WO2018058531A1 - Target tracking method and device, and image processing apparatus - Google Patents

Abstract

A target tracking method and device, and image processing apparatus. The target tracking method comprises: determining, according to predetermined scaling factors, multiple different sizes of a monitoring target; for each of the current sizes, calculating feature vector distances between a reference block of the monitoring target and one or more candidate blocks of the monitoring target in a current frame, and determining, according to the feature vector distances, a matching value and candidate block of said current size; and determining, according to the matching value and candidate block of each of the different sizes, a tracking result of the monitoring target in the current frame. In this way, the present invention maintains precision of target tracking regardless of a significant size change of a monitoring target in an image frame.

Description

Target tracking method, device and image processing device Technical field

Embodiments of the present invention relate to the field of graphic image technologies, and in particular, to a target tracking method and apparatus, and an image processing apparatus.

Background technique

In the field of video surveillance, it is generally necessary to detect an object of interest. For example, in vehicle detection in a parking lot, real-time monitoring of vehicles appearing in the video is required. It is currently possible to track the objects in the video; where the moving object is moving, the size in the image frame may change.

It should be noted that the above description of the technical background is only for the purpose of facilitating a clear and complete description of the technical solutions of the present invention, and is convenient for understanding by those skilled in the art. The above technical solutions are not considered to be well known to those skilled in the art simply because these aspects are set forth in the background section of the present invention.

Summary of the invention

However, the inventors have found that the current target tracking scheme does not take into account the change in the size of the detection target, if the detection target is significantly enlarged or reduced in the image frame (for example, the vehicle on the highway facing the surveillance camera is in the image) The size in the frame will become larger), which will reduce the accuracy of the target tracking.

Embodiments of the present invention provide a target tracking method, apparatus, and image processing apparatus, and it is expected that the accuracy of target tracking is not reduced even if the detection target is significantly enlarged or reduced in the image frame.

According to a first aspect of the embodiments of the present invention, a target tracking method is provided to track a detection target in a video, where the target tracking method includes:

Determining a plurality of different sizes of the detection target according to a predetermined scaling factor;

For each current size, calculating a feature vector distance between the reference block of the detection target and one or more candidate blocks of the detection target in the current frame, and determining a match of the current size according to the feature vector distance Value and candidate block;

And determining, according to the plurality of different size matching values and candidate blocks, a tracking result of the detection target in the current frame.

According to a second aspect of the embodiments of the present invention, there is provided a target tracking device for detecting a target in a video Tracking, the target tracking device includes:

a size determining unit that determines a plurality of different sizes of the detection target according to a predetermined scaling factor;

a candidate determining unit that calculates, for each current size, a feature vector distance between the reference block of the detection target and one or more candidate blocks of the detection target in the current frame, and determines the distance according to the feature vector distance a matching value of the current size and a candidate block;

a result determining unit that determines a tracking result of the detection target in the current frame according to the plurality of different size matching values and candidate blocks.

According to a third aspect of the embodiments of the present invention, there is provided an image processing apparatus, wherein the image processing apparatus comprises a target tracking device as described above.

According to still another aspect of an embodiment of the present invention, a computer readable program is provided, wherein when the program is executed in a target tracking device or an image processing device, the program causes the target tracking device or image processing device to perform the above The target tracking method.

According to still another aspect of an embodiment of the present invention, a storage medium storing a computer readable program, wherein the computer readable program causes a target tracking device or an image processing device to perform a target tracking method as described above.

An advantageous effect of the embodiment of the present invention is to separately calculate a feature vector distance between a reference block of a detection target and one or more candidate blocks of the detection target in a current frame for a plurality of different sizes, and according to the feature vector distance Determining a matching value of the current size and a candidate block; determining a tracking result of the detection target in the current frame according to the matching values of the plurality of different sizes and the candidate block. Thus, even if the detection target is significantly enlarged or reduced in the image frame, the accuracy of the target tracking is not lowered.

Specific embodiments of the present invention are disclosed in detail with reference to the following description and the drawings, in which <RTIgt; It should be understood that the embodiments of the invention are not limited in scope. The embodiments of the present invention include many variations, modifications, and equivalents within the scope of the appended claims.

Features described and/or illustrated with respect to one embodiment may be used in one or more other embodiments in the same or similar manner, in combination with, or in place of, features in other embodiments. .

It should be emphasized that the term "comprising" or "comprises" or "comprising" or "comprising" or "comprising" or "comprising" or "comprises"

DRAWINGS

Many aspects of the invention can be better understood with reference to the following drawings. The components in the figures are not drawn to scale, but only to illustrate the principles of the invention. In order to facilitate the illustration and description of some parts of the invention, the corresponding parts in the figures may be enlarged or reduced.

Elements and features described in one of the figures or one embodiment of the invention may be combined with elements and features illustrated in one or more other figures or embodiments. In the accompanying drawings, like reference numerals refer to the

1 is a schematic diagram of a target tracking method according to Embodiment 1 of the present invention;

2 is a schematic diagram of calculating a matching value and a candidate block for a certain size according to Embodiment 1 of the present invention;

3 is a schematic diagram of a search window according to Embodiment 1 of the present invention;

4 is a schematic diagram of a candidate candidate block according to Embodiment 1 of the present invention;

Figure 5 is a schematic diagram of a target tracking device according to Embodiment 2 of the present invention;

6 is another schematic diagram of a target tracking device according to Embodiment 2 of the present invention;

7 is a schematic diagram of a candidate determining unit according to Embodiment 2 of the present invention;

8 is a schematic diagram of a vector generation unit according to Embodiment 2 of the present invention;

9 is a schematic diagram of a vector construction unit according to Embodiment 2 of the present invention;

Figure 10 is a schematic diagram of a result determining unit of Embodiment 2 of the present invention;

Figure 11 is a diagram showing an image processing apparatus according to a third embodiment of the present invention.

detailed description

The foregoing and other features of the present invention will be apparent from the The specific embodiments of the present invention are disclosed in the specification and the drawings, which are illustrated in the embodiment of the invention The invention includes all modifications, variations and equivalents falling within the scope of the appended claims.

Example 1

Embodiments of the present invention provide a target tracking method for tracking a detection target in a video.

1 is a schematic diagram of a target tracking method according to an embodiment of the present invention. As shown in FIG. 1, the target tracking method includes:

Step 101: Determine a plurality of different sizes of the detection target according to a predetermined scaling factor;

Step 102: Calculate, for each current size, a feature vector distance between the reference block of the detection target and one or more candidate blocks of the detection target in the current frame, and determine the current according to the feature vector distance The matching value of the size and the candidate block;

Step 103: Determine, according to the plurality of different size matching values and candidate blocks, a tracking result of the detection target in the current frame.

In this embodiment, the plurality of different sizes may include: normal size, reduced size, and enlarged size. For example, multiplying the normal size by a predetermined reduction factor (eg, 0.95) may result in a downsizing, and multiplying the normal size by a predetermined magnification factor (eg, 1.05) may result in an enlarged size. However, the present invention is not limited thereto, and the scaling factor may be determined according to actual needs, and may also have a plurality of different sizes.

The following description will be made by taking only three types of normal size, reduced size, and enlarged size.

In the present embodiment, the matching value and the candidate block can be calculated for each size, and how the calculation can be as described later. The matching values of the plurality of different sizes may then be compared; and the candidate block corresponding to the minimum matching value is determined as the tracking block of the detection target in the current frame.

Thus, the embodiment of the present invention considers a case where the size of the detection target changes, and the accuracy of the target tracking is not lowered even if the detection target is significantly enlarged or reduced in the image frame.

The following takes the normal size as an example to illustrate how to calculate the matching value and the candidate block.

FIG. 2 is a schematic diagram of calculating a matching value and a candidate block for a certain size according to an embodiment of the present invention. As shown in FIG. 2, the process may include:

Step 201: Determine a reference block of the detection target for the current size.

In this embodiment, the initial position (x, y, w, h) of the target to be tracked may be acquired in a frame of the video (eg, the previous frame of the current frame); wherein x is the upper left pixel of the frame containing the target The horizontal coordinate, y is the vertical coordinate of the pixel in the upper left corner of the box containing the target, w is the width of the frame containing the target, and h is the height of the frame containing the target. In the frame of the initial video, the image in which the frame containing the target is located may be extracted as a reference block.

Step 202: Determine a horizontal sampling interval and a vertical sampling interval according to the size of the reference block.

In this embodiment, a parameter min_dim may be first set, then the short side SE=min(w,h) of the tracking target (ie, the corresponding reference block) is obtained, and the long side of the tracking target is obtained LE=max(w,h). . If the short side SE is smaller than min_dim, the short side sampling interval SDS=1 is set, otherwise SDS=round(SE/min_dim) is set, where round() indicates rounding operation. In addition, the sampling interval of the long side is set to SDL=round (SDS*LE/SE).

Then, you can set the horizontal sampling interval of the tracking target SDH=w<h? SDS: SDL, set the tracking target The target vertical sampling interval SDV=w>h? SDS: SDL.

It is to be noted that the above only schematically shows how to set the horizontal sampling interval SDH and the vertical sampling interval SDV, but the present invention is not limited thereto, and may be set in other manners.

Step 203: Set a search window in the current frame according to a position of the reference block, the horizontal sampling interval, and the vertical sampling interval.

In this embodiment, for the current frame, a search window may be set around the location where the tracking target obtained in the previous frame (for example, the corresponding reference block) is located. For example, you can first set a parameter search_range, the horizontal range of the search window is from –SDH*search_range+x to SDH*search_range+x+w, and the vertical range of the search window is from –SDV*search_range+y to SDV*search_range+y+h .

3 is a schematic diagram of a search window according to an embodiment of the present invention. As shown in FIG. 3, a search window in a current frame may be disposed around a reference block.

It should be noted that the above only schematically shows how to set the search window, but the present invention is not limited thereto, and may be set in other manners. By setting the search window, you can reduce the amount of calculation without reducing the accuracy of the search.

Step 204: Extract one or more candidate blocks from the search window according to the size of the reference block, the horizontal sampling interval, and the vertical sampling interval.

In this embodiment, for example, a block of the same size as the reference block may be sequentially extracted as a candidate block in the search window, the horizontal extraction interval is SDH, and the vertical extraction interval is SDV.

FIG. 4 is a schematic diagram of a candidate candidate block according to an embodiment of the present invention. As shown in FIG. 4, one or more candidate blocks may be extracted in a search window. It should be noted that the above only schematically shows how to extract candidate blocks, but the present invention is not limited thereto, and may be set in other manners. By sampling the candidate block or the reference block, the amount of calculation can be reduced without degrading the accuracy of the search.

Step 205: Generate a feature vector for each candidate block and the reference block.

In this embodiment, specifically for a certain candidate block or a reference block, the pixels in the block may be sampled according to the horizontal sampling interval and the vertical sampling interval; and the plurality of pixels obtained by sampling are used. The feature value constructs a feature vector of the block.

The feature vector may include the following: a gray feature vector and a HG (Histogram of Oriented Gradient) feature vector, but the present invention is not limited thereto, and for example, other feature vectors may also be employed.

In this embodiment, the gray value of the sampled plurality of pixels may be configured as a gray feature vector; the HoG value of the sampled plurality of pixels is configured as a HoG feature vector; and then the gray feature vector sum is The HoG feature vectors are combined to obtain a feature vector of the candidate block or the reference block.

For example, for a certain candidate block, sampling may be performed within the candidate block, the horizontal sampling interval is, for example, 2*SDH, and the vertical sampling interval is, for example, 2*SDV. The gradation values of the plurality of sampled pixel points are sequentially arranged to form a gradation feature vector. Then, the HoG features are calculated for the sampled pixels, and the obtained HoG feature vectors are combined with the gray feature vectors to obtain a final block feature vector.

In addition, a weight coefficient may be respectively assigned to the gray feature vector and the HoG feature vector; and the gray feature vector and the HoG feature vector given the weight coefficient are combined. For example, in the final feature vector, the gray feature vector obtains the weight of Wy, and the HoG feature vector obtains the weight of Wh.

For the reference block, the same processing can be performed. Thus one feature vector can be obtained for the reference block, and one feature vector can also be obtained for each candidate block.

Step 206: Calculate a vector distance between a feature vector of the reference block and a feature vector of each candidate block.

In the present embodiment, regarding how to calculate the vector distance between two feature vectors, reference can be made to the related art.

Step 207, determining a candidate block having the smallest vector distance between the feature vectors of the reference block as the tracking block of the current size;

In step 208, the smallest vector distance is taken as the matching value of the current size.

For example, the position of the candidate block having the smallest vector distance from the reference block may be determined as the tracking result under the current size, and the vector distance from which the vector distance of the reference block is the smallest may be determined as the matching value under the current size.

It is to be noted that FIG. 2 is only illustrative of an embodiment of the invention, but the invention is not limited thereto. For example, the order of execution between the various steps can be appropriately adjusted, and other steps can be added or some of the steps can be reduced. Those skilled in the art can appropriately modify the above based on the above contents, and are not limited to the description of the above drawings.

Thereby, for example, a matching value in a normal size and a candidate block can be calculated. Then, through the above steps 201 to 208, the matching values and the candidate blocks in the reduced size and the enlarged size can be respectively calculated.

For example, the tracking target can be scaled to a smaller size (for example, 0.95 of the normal size), and the center of the small-sized target is consistent with the center position of the normal-sized target, and the length and width are respectively the length and width of the normal-sized target multiplied by one less than one. The coefficient (for example, 0.95) scales the reference block to the same size.

Then, steps 201 to 208 are repeated to calculate the matching value and tracking result of the target in a small size. If the matching value is smaller than the matching value under the normal size, the matching value and the tracking result are obtained in a small size to replace the matching value and the tracking result under the normal size; otherwise, the matching value and the tracking result under the normal size are retained.

For another example, the tracking target is scaled to a larger size (for example, 1.05 of the normal size), and the center of the large-sized target is consistent with the center position of the normal-sized target, and the length and width are respectively the length and width of the normal-sized target multiplied by one greater than one. The coefficient (for example, 1.05) scales the reference block to the same size.

Then, steps 201 to 208 are repeated to calculate the matching value and tracking result of the target under a large size. If the matching value is smaller than the previously retained matching value, the matching value and the tracking result are used to replace the previous matching value and the tracking result, otherwise, the previous matching value and the tracking result are retained.

It should be noted that the above only describes the three types of normal size, reduced size, and enlarged size. However, the present invention is not limited thereto, and may be three or more sizes, and the like; specific embodiments may be determined as needed.

In this embodiment, the reference block may also be updated by using the information of the tracking block.

For example, the block in which the obtained tracking result is located is scaled to the size of the reference block, and then the reference block is updated according to the information of the reference block (for example, the gray value) and the information of the block in which the tracking result is located (for example, the gray value). Further, the result of performing weighted averaging may be used to update the reference block.

For example, Ref=learing_rate*Ref+(1-learing_rate)*Trk. Where Ref represents the information of the reference block, learing_rate represents the weight coefficient, and Trk represents the information of the block in which the tracking result is located.

As can be seen from the above embodiment, the reference vector of the detection target and the feature vector distance of the detection target between one or more candidate blocks in the current frame are respectively calculated for a plurality of different sizes, and the current size is determined according to the feature vector distance. a matching value and a candidate block; determining a tracking result of the detection target in the current frame according to the plurality of different size matching values and the candidate block. Thus, even if the detection target is significantly enlarged or reduced in the image frame, the accuracy of the target tracking is not lowered.

Example 2

Embodiments of the present invention provide a target tracking apparatus that tracks a detection target in a video. This embodiment 2 corresponds to the target tracking method of Embodiment 1, and the same content will not be described again.

FIG. 5 is a schematic diagram of a target tracking device according to an embodiment of the present invention. As shown in FIG. 5, the target tracking device 500 includes:

a size determining unit 501, which determines a plurality of different sizes of the detection target according to a predetermined scaling factor;

a candidate determining unit 502, for each current size, calculating a feature vector distance between the reference block of the detection target and one or more candidate blocks of the detection target in the current frame, and determining according to the feature vector distance a matching value of the current size and a candidate block;

The result determining unit 503 determines the tracking result of the detection target in the current frame according to the plurality of different size matching values and the candidate block.

In the present embodiment, the plurality of different sizes include: normal size, reduced size, and enlarged size; however, the invention is not limited thereto.

6 is another schematic diagram of a target tracking device according to an embodiment of the present invention. As shown in FIG. 6, the target tracking device 600 includes a size determining unit 501, a candidate determining unit 502, and a result determining unit 503, as described above.

As shown in FIG. 6, the target tracking device 600 may further include:

a reference block determining unit 601 that determines the reference block of the detection target for the current size;

An interval determining unit 602 determines a horizontal sampling interval and a vertical sampling interval according to the size of the reference block.

As shown in FIG. 6, the target tracking device 600 may further include:

The reference block update unit 603 updates the reference block with information of the tracking block.

FIG. 7 is a schematic diagram of a candidate determining unit 502 according to an embodiment of the present invention. As shown in FIG. 7, the candidate determining unit 502 may include:

a window setting unit 701, which sets a search window in the current frame according to a position of the reference block, the horizontal sampling interval, and the vertical sampling interval;

a candidate block extracting unit 702, which extracts one or more candidate blocks from the search window according to the size of the reference block, the horizontal sampling interval, and the vertical sampling interval;

a vector generation unit 703 that generates a feature vector for each candidate block and the reference block;

A distance calculation unit 704 that calculates a vector distance between a feature vector of the reference block and a feature vector of each candidate block.

As shown in FIG. 7, the candidate determining unit 502 may further include:

a candidate block determining unit 705 that determines a candidate block having a smallest vector distance from a feature vector of the reference block as the tracking block of the current size;

The matching value determining unit 706 takes the smallest vector distance as the matching value of the current size.

FIG. 8 is a schematic diagram of a vector generating unit 703 according to an embodiment of the present invention. As shown in FIG. Element 703 can include:

a pixel sampling unit 801, which samples pixels in the candidate block or the reference block according to the horizontal sampling interval and the vertical sampling interval;

A vector construction unit 802 constructs a feature vector of the candidate block or the reference block using the sampled feature values of the plurality of pixels.

FIG. 9 is a schematic diagram of a vector construction unit 802 according to an embodiment of the present invention. As shown in FIG. 9, the vector construction unit 802 may include:

a first vector construction unit 901, which constructs the gray value of the sampled plurality of pixels into a grayscale feature vector;

a second vector construction unit 902 configured to construct a directional gradient histogram value of the plurality of pixels obtained as a directional gradient histogram feature vector;

A vector merging unit 903 combines the gradation feature vector and the directional gradient histogram feature vector to obtain a feature vector of the candidate block or the reference block.

As shown in FIG. 9, the vector construction unit 802 may further include:

a weight assigning unit 904, which assigns weight coefficients to the grayscale feature vector and the direction gradient histogram feature vector, respectively;

And the vector merging unit 903 is further configured to combine the gradation feature vector after the weighting coefficient and the directional gradient histogram feature vector.

FIG. 10 is a schematic diagram of a result determining unit 503 according to an embodiment of the present invention. As shown in FIG. 10, the result determining unit 503 may include:

a matching value comparison unit 1001 that compares the matching values of the plurality of different sizes;

The tracking block determining unit 1002 determines the candidate block corresponding to the minimum matching value as the tracking block of the detection target in the current frame.

It is to be noted that the above is only the components related to the present invention, but the present invention is not limited thereto. The target tracking device may also include other components or modules, and reference may be made to the prior art for the specific content of these components or modules.

As can be seen from the above embodiment, the reference vector of the detection target and the feature vector distance of the detection target between one or more candidate blocks in the current frame are respectively calculated for a plurality of different sizes, and the current size is determined according to the feature vector distance. a matching value and a candidate block; determining a tracking result of the detection target in the current frame according to the plurality of different size matching values and the candidate block. Thus, even if the detection target is significantly enlarged in the image frame or Zooming out does not reduce the accuracy of the target tracking.

Example 3

An embodiment of the present invention provides an image processing device including the target tracking device as described in Embodiment 2.

Figure 11 is a schematic diagram of an image processing apparatus according to an embodiment of the present invention. As shown in FIG. 11, the image processing apparatus 1100 may include a central processing unit (CPU) 100 and a memory 110; the memory 110 is coupled to the central processing unit 100. The memory 110 can store various data; in addition, a program for information processing is stored, and the program is executed under the control of the central processing unit 100.

In one embodiment, the functionality of the target tracking device 500 or 600 can be integrated into the central processor 100. Wherein, the central processing unit 100 can be configured to implement the target tracking method as described in Embodiment 1.

In another embodiment, the target tracking device 500 or 600 can be configured separately from the central processing unit 100. For example, the target tracking device 500 or 600 can be configured as a chip connected to the central processing unit 100, controlled by the central processing unit 100. The function of the target tracking device 500 or 600 is achieved.

In this embodiment, the central processing unit 100 may be configured to perform control of determining a plurality of different sizes of the detection target according to a predetermined scaling factor; for each current size, calculating a reference block of the detection target and And detecting a feature vector distance between one or more candidate blocks in the current frame, and determining a matching value of the current size and a candidate block according to the feature vector distance; and matching values according to the multiple different sizes And a candidate block, determining a tracking result of the detection target in the current frame.

In addition, as shown in FIG. 11, the image processing apparatus 1100 may further include: an input/output (I/O) device 120, a display 130, and the like; wherein the functions of the above components are similar to those of the prior art, and are not described herein again. It is to be noted that the image processing apparatus 1100 does not necessarily have to include all of the components shown in FIG. 11; further, the image processing apparatus 1100 may further include components not shown in FIG. 11, and reference may be made to the related art.

An embodiment of the present invention provides a computer readable program, wherein when the program is executed in a target tracking device or an image processing device, the program causes the target tracking device or the image processing device to perform the method as described in Embodiment 1. Target tracking method.

An embodiment of the present invention provides a storage medium storing a computer readable program, wherein the computer readable program causes a target tracking device or an image processing device to perform the target tracking method as described in Embodiment 1.

The above apparatus and method of the present invention may be implemented by hardware or by hardware in combination with software. this invention Reference is made to a computer readable program that, when executed by a logic component, enables the logic component to implement the apparatus or components described above, or to implement the various methods or steps described above. . The present invention also relates to a storage medium for storing the above program, such as a hard disk, a magnetic disk, an optical disk, a DVD, a flash memory, or the like.

The method/apparatus described in connection with the embodiments of the invention may be embodied directly in hardware, a software module executed by a processor, or a combination of both. For example, one or more of the functional block diagrams shown in FIG. 5 and/or one or more combinations of functional block diagrams (eg, a size determining unit, a candidate determining unit, a result determining unit, etc.) may correspond to a computer program. Each software module of the process may also correspond to each hardware module. These software modules may correspond to the respective steps shown in FIG. 1, respectively. These hardware modules can be implemented, for example, by curing these software modules using a Field Programmable Gate Array (FPGA).

The software module can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art. A storage medium can be coupled to the processor to enable the processor to read information from, and write information to, the storage medium; or the storage medium can be an integral part of the processor. The processor and the storage medium can be located in an ASIC. The software module can be stored in the memory of the mobile terminal or in a memory card that can be inserted into the mobile terminal. For example, if a device (such as a mobile terminal) uses a larger capacity MEGA-SIM card or a large-capacity flash memory device, the software module can be stored in the MEGA-SIM card or a large-capacity flash memory device.

One or more of the functional blocks described in the figures and/or one or more combinations of functional blocks may be implemented as a general purpose processor, digital signal processor (DSP) for performing the functions described herein. An application specific integrated circuit (ASIC), field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware component, or any suitable combination thereof. One or more of the functional blocks described with respect to the figures and/or one or more combinations of functional blocks may also be implemented as a combination of computing devices, eg, a combination of a DSP and a microprocessor, multiple microprocessors One or more microprocessors in conjunction with DSP communication or any other such configuration.

The present invention has been described in connection with the specific embodiments thereof, and it should be understood by those skilled in the art that A person skilled in the art can make various modifications and changes to the present invention within the scope of the present invention.

Claims (20)

A target tracking method for tracking a detection target in a video, the target tracking method includes: Determining a plurality of different sizes of the detection target according to a predetermined scaling factor; For each current size, calculating a feature vector distance between the reference block of the detection target and one or more candidate blocks of the detection target in the current frame, and determining a match of the current size according to the feature vector distance Value and candidate block; And determining, according to the plurality of different size matching values and candidate blocks, a tracking result of the detection target in the current frame. The target tracking method according to claim 1, wherein the plurality of different sizes comprise: a normal size, a reduced size, and an enlarged size. The target tracking method according to claim 1, wherein the target tracking method further comprises: Determining the reference block of the detection target for the current size; The horizontal sampling interval and the vertical sampling interval are determined according to the size of the reference block. The target tracking method according to claim 3, wherein calculating a feature vector distance between the reference block of the detection target and the one or more candidate blocks of the detection target in the current frame comprises: Setting a search window in the current frame according to a position of the reference block, the horizontal sampling interval, and the vertical sampling interval; Extracting one or more candidate blocks from the search window according to a size of the reference block, the horizontal sampling interval, and the vertical sampling interval; Generating a feature vector for each candidate block and the reference block; A vector distance between a feature vector of the reference block and a feature vector of each candidate block is calculated. The target tracking method according to claim 4, wherein determining the matching value of the current size and the candidate block according to the feature vector distance comprises: A candidate block that minimizes a vector distance between feature vectors of the reference block is determined as the tracking block of the current size; The smallest vector distance is taken as the matching value of the current size. The target tracking method according to claim 4, wherein generating a feature vector for each candidate block and the reference block comprises: Sampling the candidate block or the pixels in the reference block according to the horizontal sampling interval and the vertical sampling interval; The feature vector of the candidate block or the reference block is constructed using the sampled feature values of the plurality of pixels. The target tracking method according to claim 6, wherein the constructing the feature vector of the candidate block or the reference block by using the sampled feature values of the plurality of pixels comprises: Constructing the gray value of the sampled plurality of pixels into a grayscale feature vector; Constructing a direction gradient histogram value of the sampled plurality of pixels into a direction gradient histogram feature vector; Combining the grayscale feature vector and the direction gradient histogram feature vector to obtain a feature vector of the candidate block or the reference block. The target tracking method according to claim 7, wherein the target tracking method further comprises: And assigning weight coefficients to the grayscale feature vector and the direction gradient histogram feature vector respectively; And merging the grayscale feature vector and the direction gradient histogram feature vector after the weighting coefficient. The target tracking method according to claim 1, wherein determining the tracking result of the detection target in the current frame according to the matching values of the plurality of different sizes and the candidate block comprises: Comparing the matching values of the plurality of different sizes; The candidate block corresponding to the minimum matching value is determined as the tracking block of the detection target in the current frame. The target tracking method according to claim 9, wherein the target tracking method further comprises: The reference block is updated with information of the tracking block. A target tracking device that tracks a detection target in a video, the target tracking device comprising: a size determining unit that determines a plurality of different sizes of the detection target according to a predetermined scaling factor; a candidate determining unit that calculates, for each current size, a feature vector distance between the reference block of the detection target and one or more candidate blocks of the detection target in the current frame, and determines the distance according to the feature vector distance a matching value of the current size and a candidate block; a result determining unit that determines a tracking result of the detection target in the current frame according to the plurality of different size matching values and candidate blocks. The target tracking device of claim 11, wherein the plurality of different sizes comprise: normal size, reduced size, and enlarged size. The target tracking device according to claim 11, wherein the target tracking device further comprises: a reference block determining unit that determines the reference block of the detection target for the current size; An interval determining unit that determines a horizontal sampling interval and a vertical sampling interval according to a size of the reference block. The target tracking device according to claim 13, wherein the candidate determining unit comprises: a window setting unit that sets a search window in the current frame according to a position of the reference block, the horizontal sampling interval, and the vertical sampling interval; a candidate block extracting unit that extracts one or more candidate blocks from the search window according to a size of the reference block, the horizontal sampling interval, and the vertical sampling interval; a vector generation unit that generates a feature vector for each candidate block and the reference block; A distance calculation unit that calculates a vector distance between a feature vector of the reference block and a feature vector of each candidate block. The target tracking device according to claim 14, wherein the candidate determining unit further comprises: a candidate block determining unit that determines a candidate block having a smallest vector distance from a feature vector of the reference block as the tracking block of the current size; A matching value determining unit that takes the smallest vector distance as the matching value of the current size. The target tracking device according to claim 14, wherein the vector generating unit comprises: a pixel sampling unit that samples pixels in the candidate block or the reference block according to the horizontal sampling interval and the vertical sampling interval; A vector construction unit that constructs a feature vector of the candidate block or the reference block using the sampled feature values of the plurality of pixels. The target tracking device according to claim 16, wherein the vector construction unit comprises: a first vector construction unit that constructs the gray value of the sampled plurality of pixels into a grayscale feature vector; a second vector construction unit that constructs the direction gradient histogram values of the plurality of pixels obtained by the sampling into a direction gradient histogram feature vector; a vector merging unit that combines the gradation feature vector and the directional gradient histogram feature vector to obtain a feature vector of the candidate block or the reference block. The target tracking device according to claim 11, wherein the result determining unit comprises: a matching value comparison unit that compares the matching values of the plurality of different sizes; A tracking block determining unit that determines a candidate block corresponding to the minimum matching value as a tracking block of the detection target in the current frame. The target tracking device of claim 18, wherein the target tracking device further comprises: A reference block update unit that updates the reference block with information of the tracking block. An image processing apparatus, wherein the image processing apparatus comprises the object tracking device according to claim 11.

Images