CN104980732B - The system and method for measuring the potential eye fatigue of stereoscopic motion picture - Google Patents

Abstract

A system and method for measuring potential eyestrain experienced by a viewer while viewing a 3D presentation (eg, stereoscopic motion picture) is provided. The eyestrain measurement system and method of the present disclosure are based on the measurement of disparity (or depth) and disparity transformation of 3D rendered stereoscopic images. The disclosed systems and methods provide for acquiring a first image and a second image (202) from a first segment, estimating (204) the disparity of at least one point in the first image to at least one corresponding point in the second image, estimating The disparity transformation of the sequence of first and second images (206), and the potential eyestrain experienced while viewing the 3D presentation is determined based on the disparity and the disparity transformation of the sequence of first and second images (208).

Description

System and method for measuring potential eyestrain of stereoscopic motion picture

Cross References to Related Applications

The present invention is a divisional application of an invention patent application entitled "System and Method for Measuring Potential Eye Fatigue of Stereoscopic Motion Pictures" with the filing date of May 12, 2008 and the application number of 200880129158.1.

technical field

The present disclosure relates generally to computer graphics processing and display systems, and more particularly to a system and method for measuring potential eyestrain experienced by a viewer viewing a three-dimensional (3D) presentation (eg, stereoscopic motion picture).

Background technique

Stereoscopic imaging is the process of visually combining at least two images of a scene taken from slightly different viewpoints in order to create the illusion of three-dimensional depth. This technique relies on the fact that human eyes are separated by a distance, and therefore do not view the exact same scene. By providing each eye with an image from a different perspective, the viewer's eyes are tricked into perceiving depth. Typically, where two distinct points of view are provided, the constituent images are referred to as the "left" and "right" images, respectively, also known as the reference image and the supplementary image, respectively. However, those skilled in the art will recognize that more than two viewpoints may be combined to form a stereoscopic image.

In 3D post-production, VFX workflow, and 3D rendering applications, an important process is to infer a depth map from a stereoscopic image consisting of a left-eye view image and a right-eye view image, in order to create stereoscopic motion pictures. For example, recently commercialized autostereoscopic 3D displays require an image-plus-depth-map input format so that the display can generate different 3D views to support multiple viewing angles.

The process of inferring a depth map from a stereo pair of images is known in the field of computer vision research as stereo matching because pixel or block matching is used to find corresponding points in the left and right eye view images. A depth value is inferred from the relative distance between two pixels in each image corresponding to the same point in the scene.

Widespread in many computer vision applications such as, for example, fast object modeling and prototyping for computer-aided drafting (CAD), object segmentation and detection for human-computer interaction (HCI), video compression, and visual surveillance (visual surveillance) Stereo matching of digital images is used in order to provide three-dimensional (3D) depth information. Stereo matching obtains images of a scene from two or more cameras at different positions and orientations in the scene. These digital images are acquired from each camera at about the same time, and points in each image are matched corresponding to 3D points in space. Typically, points in one image are associated with points in another image by searching a portion of the image and matching points from different images using constraints, such as epipolar constraints. The matched image and depth map can then be used to create stereoscopic 3D motion pictures.

One of the main problems with current stereoscopic 3D motion pictures is that the viewer may experience eyestrain after watching the motion picture for a certain period of time. Therefore, when directors make 3D movies, they have to consider how to shoot scenes or edit movies in such a way that the eye strain experienced by the audience is minimized. This is part of the reason why making 3D motion graphics is more complex and time-consuming than making traditional 2D motion graphics.

The challenge of producing 3D motion pictures is that it is very difficult for directors and editors to visually assess the potential eye strain experienced by the audience. There are several factors that contribute to this difficulty. First, because eye strain is a cumulative effect over the course of viewing motion, the director or editor has to watch 3D motion long enough to experience eye strain. Because a small number of fragments usually do not cause eyestrain. Second, eye strain can also be caused by sudden depth changes between two clips. When editors connect clips during editing, they struggle to gauge potential eye strain caused by sudden depth changes. They will need to use a time-consuming trial-and-error process to connect the different pieces and "feel" the potential eye strain caused by the depth transition.

Therefore, there is a need for a technique that can measure perceived potential eye strain while viewing a 3D presentation such as stereoscopic motion picture. Furthermore, there is a need for an automated system and method that can measure potential eyestrain during the process of editing 3D motion picture.

Contents of the invention

A system and method for measuring potential eyestrain experienced by a viewer while viewing a 3D presentation (eg, stereoscopic motion picture) is provided. The systems and methods of the present disclosure take into account that the distance between the eye's point of convergence and the focal point when viewing a 3D presentation is closely related to the depth of the focused object, which is also related to the disparity of the object's pixels. The eyestrain measurement system and method of the present disclosure are based on the measurement of disparity (or depth) and disparity transformation of 3D rendered stereoscopic images. The disclosed technology is useful for directors and editors to efficiently create comfortable 3D movies.

According to one aspect of the present disclosure, there is provided a method of measuring potential eyestrain experienced while viewing a three-dimensional (3D) presentation, the method comprising acquiring a first image and a second image from a first segment; estimating disparity of at least one point of at least one corresponding point in the second image; estimating a disparity transformation of the sequence of first and second images; Potential eye fatigue experienced when

In another aspect, the estimating disparity conversion step includes: estimating the disparity of the last frame of the previous segment; estimating the disparity of the first frame of the first segment; and determining the disparity of the last frame of the previous segment and the first frame of the first segment The difference between parallax.

In one aspect, the estimating disparity transformation step includes: estimating disparity within each of the plurality of frames of the first segment; and determining a difference between the disparities of each frame of the first segment.

In another aspect, the step of determining potential eyestrain further includes determining an instantaneous eyestrain function for each frame of the sequence of first and second images.

In another aspect, the step of determining potential eyestrain further includes applying an attenuation factor to the instantaneous eyestrain function for each frame of the sequence of first and second images.

In another aspect, the step of determining potential eyestrain further includes accumulating the attenuated instantaneous eyestrain function for each frame of the sequence of first and second images over a predetermined period of time.

In another aspect, the step of determining potential eyestrain further includes saturating the eyestrain function accumulated over the sequence of first and second images.

In another aspect, the method further includes: determining whether the potential eyestrain is acceptable; and correcting the parallax of the first and second images if the potential eyestrain is not acceptable.

According to another aspect of the present disclosure, a system for measuring potential eyestrain experienced while viewing a three-dimensional (3D) presentation is provided. The system includes: means for acquiring a first image and a second image from a first segment; a disparity estimator for estimating a disparity of at least one point in the first image to at least one corresponding point in the second image; a disparity transformation estimator for estimating the disparity transformation of the sequence of first and second images; and an eye strain estimator for determining the perceived sensation while viewing the 3D presentation based on the disparity and the disparity transformation of the sequence of first and second images potential eye fatigue.

According to another aspect of the present disclosure, there is provided a program storage device readable by a machine, the program storage device tangibly embodying a program executable by a machine for performing a method for measuring a potential eye while viewing a three-dimensional (3D) presentation. A program of instructions for fatigued method steps, the method comprising: acquiring a first image and a second image from a first segment; estimating a disparity between at least one point in the first image and at least one corresponding point in the second image; estimating Parallax transformation of the sequence of first and second images; and determining potential eyestrain experienced while viewing the 3D presentation based on the disparity and the parallax transformation of the sequence of first and second images.

Description of drawings

These and other aspects, features and advantages of the present disclosure will be described or will be apparent from the following detailed description of the preferred embodiments, read in conjunction with the accompanying drawings .

In the drawings, where like reference numerals designate like elements throughout the several drawings:

FIG. 1 illustrates points of convergence and focal points experienced by a viewer or member of an audience while viewing a three-dimensional (3D) presentation;

Figure 2 illustrates the relationship of convergence distance, perceived depth, parallax and convergence angle when the convergence point is in front of the screen for displaying the 3D presentation;

Figure 3 illustrates the relationship between convergence distance, perceived depth, parallax and convergence angle when the convergence point is behind the screen;

4 is an exemplary illustration of a system for measuring eye fatigue experienced while viewing a three-dimensional (3D) presentation, according to one aspect of the present disclosure;

5 is a flowchart of an exemplary method for measuring eye fatigue experienced while viewing a three-dimensional (3D) presentation, according to one aspect of the present disclosure;

Figure 6 illustrates a sigmoid function for modeling saturation of eye fatigue perception;

FIG. 7 illustrates an eye strain measurement equation over time according to one aspect of the present disclosure; and

FIG. 8 illustrates an instant eyestrain function and an overall eyestrain measure according to one aspect of the present disclosure.

It should be understood that the drawing(s) are for purposes of illustrating the concepts of the disclosure and are not necessarily the only possible configurations for illustrating the disclosure.

detailed description

It should be understood that each element shown in the drawings may be realized in various forms of hardware, software and combinations thereof. Preferably, these elements are implemented in a combination of hardware and software on one or more suitably programmed general purpose devices which may include a processor, memory and input/output interfaces.

This description illustrates the principles of the disclosure. It will thus be appreciated that those skilled in the art will be able to devise various arrangements which, although not explicitly described or shown herein, embody the principles of the disclosure and are included within the spirit and scope of the principles.

All examples and conditional language recited herein are intended for pedagogical purposes in order to assist the reader in understanding the principles of the disclosure and concepts contributed by the inventors to advance the state of the art, and should be construed as not limiting to such specific recitations Examples and conditions.

Additionally, all statements herein reciting principles, aspects, and embodiments of the disclosure, as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. Additionally, it is intended that such equivalents include both currently known equivalents as well as equivalents developed in the future, ie, any elements developed that perform the same function, regardless of structure.

Thus, for example, it will be appreciated by those skilled in the art that the block diagrams presented herein represent conceptual views of illustrative circuitry embodying the present principles. Similarly, it will be appreciated that any flow chart, flowdiagram, state transition diagram, pseudocode, etc. representations may substantially be represented in a computer-readable medium and thus executed by a computer or processor. processing regardless of whether such a computer or processor is explicitly shown.

The functions of the various elements shown in the figures may be provided through the use of dedicated hardware as well as hardware capable of executing the software in association with appropriate software. When a processor is utilized to provide the described functionality, it may be provided with a single dedicated processor, with a single shared processor, or with multiple independent processors, some of which may be shared. Additionally, explicit use of the terms "processor" or "controller" should not be construed as referring exclusively to hardware capable of executing software, but may implicitly include, without limitation, digital signal processor ("DSP") hardware , read-only memory ("ROM"), random-access memory ("RAM"), and non-volatile memory for storing software.

Other conventional and/or custom hardware may also be included. Similarly, any switches shown in the figures are conceptual only. Their function may be carried out through the operation of program logic, through dedicated logic, through the interaction of program control and dedicated logic, or even manually, the particular technique being selectable by the implementer as more specifically understood from the context.

In its claims, any element expressed as a means for performing a specified function is intended to encompass any way of performing that function, including, for example: a) a combination of circuit elements performing that function or b) a combination with an appropriate circuit Any form of software, thus including firmware or microcode or the like, that is executed by appropriate circuitry to perform the described functions. The present disclosure defined by such claims resides in the fact that the functionality provided by the various recited elements is combined and brought together in the manner required by the claims. Any means that can provide those functions are therefore considered equivalent to those shown herein.

Typically, a stereoscopic motion picture consists of a sequence of left-eye and right-eye pictures. For cinema applications, viewers typically have to wear 3D glasses (eg, polarized or shutter glasses) to view the 3D presentation. For displays without glasses, although the mechanism of 3D display is different, the principle of 3D perception is the same. That is, the 3D system will make the left eye see the left eye image, and the right eye only see the right eye image. The human brain is able to combine these two images in order to correctly perceive a 3D scene. However, this system can potentially cause eye muscle fatigue and eye strain for two reasons:

1. The convergence point and focus of the eyes are different. When we watch a real 3D scene, the focal point of our eyes is roughly the same as the point of convergence. However, when we watch a 3D movie, the focal point 10 of our eyes has to be always on the screen 12, and the point of convergence 14 of our eyes has to be in front or behind the screen 12 in order to perceive the correct 3D scene, as shown in Figure 1 Show. This difference is a major factor that promotes fatigue of the eye muscles and thus causes eye fatigue.

2. Depth changes of objects in 3D motion pictures. When the depth of an object changes, our eyes have to adjust the point of convergence to perceive the correct 3D effect while maintaining focus on the screen. If the depth changes are frequent and sudden, our eyes have to change the point of convergence frequently, causing fatigue of the eye muscles.

So, in a nutshell, eyestrain is mainly caused by two causes: 1) the distance between the point of convergence and the focal point of the eyes (i.e., the convergence distance 16 as shown in FIG. 1 ); and 2) a change in the point of convergence 14 . Therefore, the measurement of eye fatigue needs to consider the above two factors.

The present disclosure provides a system and method for measuring potential eyestrain experienced by a viewer while viewing a 3D presentation (eg, stereoscopic motion picture). The eyestrain measurement system and method of the present disclosure are based on the measurement of disparity (or depth) and disparity transformation. This solution is useful for directors and editors to efficiently produce good and comfortable 3D movies.

The systems and methods of the present disclosure consider that the distance between the point of convergence and the focal point of the viewer's eyes is closely related to the depth of the object in focus in the 3D rendering, which is also the parallax of the object's pixels in the 3D rendering related. Figure 2 shows the relationship of the variables involved in viewing a 3D presentation. It can be seen that given the convergence distance (Cd) 16, perceived depth (Dp) 18, audience distance (Ad) 20, convergence angle (Ca) 22, eye distance (Ed) 24 and parallax (Ds) 26, there exists the following relationship.

1. The relationship between Cd, Dp and Ad: Ad=Cd+Dp

2. The relationship between Cd, Ds, Ad and Ed: Cd(1/Ds+1/Ed)=Ad/Ed

3. The relationship between Ca, Ed, Ad and Cd: Cd=2atan(Ed/(2(Ad-Cd)))

When the point of convergence is behind the screen as shown in Figure 3, these relationships hold true as long as negative parallax and negative convergence distances are allowed. For a particular audience, eye distance (Ed) 24 and audience distance (Ad) 20 are constant during presentation, while convergence distance (Cd) 16, perceived depth (Dp) 18, convergence angle (Ca) 22 and parallax ( Ds) 26 changes during a moving picture. Based on these relationships, the calculation of the convergence point can be reduced to the estimation of depth or disparity. This results in a simpler estimation algorithm. Because many disparity estimation algorithms exist, traditional disparity measurements can be used for eye strain estimation.

Referring now to FIG. 4 , exemplary system components are shown in accordance with an embodiment of the present disclosure. A scanning device 103 may be provided for scanning a film print 104 (eg camera negative) into a digital format (eg Cineon format or SMPTE DPX file). The scanning device 103 may comprise, for example, a telecine or any device that will generate a video output from film (such as, for example, an Arri LocPro ^™ with a video output). Alternatively, files 106 (eg, files already in computer-readable form) from post-production processes or digital cinema can be used directly. Potential sources of computer readable files are AVID ^™ Clipper, DPX files, D5 tapes.

The scanned film print is input to a post-processing device 102 (eg, a computer). The computer is implemented on any of the various known computer platforms having hardware such as one or more central processing units (CPUs), such as random access memory (RAM) and/or read-only memory ( ROM), and input/output (I/O) user interface(s) 112 such as a keyboard and pointer control device (eg, mouse or joystick) and display device(s). A computer platform also includes an operating system and microinstruction code. The various processes and functions described herein may be part of the microinstruction code or part of the software application (or a combination thereof) executed via the operating system. In one embodiment, the software application is tangibly embodied on a program storage device, which can be uploaded to any suitable machine (such as post-processing device 102) and executed. In addition, various other peripheral devices can be connected to the computer platform through various interfaces and bus structures, such as parallel ports, serial ports, or Universal Serial Bus (USB). Other peripherals may include additional storage devices 124 and a printer 128 . The printer 128 may be used to print a modified version 126 of the film (eg, a stereoscopic version of the film) in which the scene or scenes may have been altered or replaced using 3D modeled objects as a result of the techniques described below.

Alternatively, the file/movie print 106 may be imported directly into the computer 102 already in a computer readable form (eg, a digital movie that may be stored on an external hard drive 124 ). Note that the term "film" as used herein may refer to film prints or digital films.

The software program includes an eyestrain measurement and reduction module 114 stored in memory 110 for measuring potential eyestrain experienced by a viewer or viewer while viewing a 3D presentation.

The eyestrain measurement and reduction module 114 includes a disparity estimator 116 configured to estimate the disparity of at least one point in the first image and at least one corresponding point in the second image (the first and second images produce a stereoscopic image pair) , and for generating a disparity map from the estimated disparity for each of at least one point in the first image and at least one corresponding point in the second image. The disparity estimator 116 includes a pixel matching cost function 132 configured to match pixels in the first and second images, and a smoothing cost function 134 for applying a smoothing constraint to the disparity estimation. The disparity estimator 116 also includes a belief propagation algorithm or function 136 for minimizing the estimated disparity, and a dynamic programming algorithm or function 138 that utilizes the determined The result of the matching function is used to initialize the belief propagation function 136 in order to speed up the belief propagation function 136 . It is to be understood that belief propagation and dynamic programming are but two exemplary methods for determining disparity and that other disparity estimation methods and algorithms may be employed by disparity estimator 116 .

A disparity transformation estimator 118 is provided for determining the transformation or change of the disparity of the stereoscopic images. An eyestrain estimator 120 is provided for estimating potential eyestrain based on the disparity map from the disparity estimator 116 and the disparity transformation of the associated images from the disparity transformation estimator 118 .

The eyestrain measurement and reduction module 114 also includes a parallax corrector 122 for adjusting the parallax between the first and second images to reduce potential eyestrain. A depth map generator 123 is also provided for converting the disparity map into a depth map by inverting the disparity values of the disparity map. In one embodiment, the depth map generator 123 works in conjunction with a parallax corrector 122 for reducing potential eye strain, as will be described below.

5 is a flowchart of an exemplary method for measuring potential eyestrain of at least two two-dimensional (2D) images according to an aspect of the present disclosure. Initially, the post-processing device 102 acquires at least two two-dimensional (2D) images, such as a stereoscopic image pair with left-eye and right-eye views (step 202 ). Post-processing device 102 may acquire at least two 2D images by obtaining a digital master image file in a computer readable format. Digital video files can be acquired by capturing a time sequence of moving images with a digital camera. Alternatively, the video sequence may be captured by a conventional film-type camera. In this scenario, the film is scanned via the scanning device 103 .

It will be appreciated that, whether the film is scanned or already in digital format, the digital file of the film will include indications or information about the location of each frame, eg, frame number, time since the start of the film, etc. Each frame of a digital image file will include an image, eg, I ₁ , I ₂ , . . . _In .

Stereoscopic images can be captured by two cameras with the same settings. Either of the cameras are calibrated to have the same focal length, focal height and parallel focal plane; or the images must be warped based on known camera parameters as if they were taken by a camera with parallel focal planes. The deflection process includes camera calibration and camera rectification. The calibration and adjustment process adjusts the epipolar lines of the stereoscopic image so that the epipolar lines are precisely the horizontal scanning lines of the image. Because correspondence point finding occurs along the epipolar lines, the calibration procedure simplifies the correspondence search to only a search along scan lines, which greatly reduces computational cost. Corresponding points are pixels corresponding to the same scene point in the image.

Next, at step 204 , a disparity map is estimated for each point in the scene (eg frame) via the disparity estimator 116 . The disparity for each scene point is calculated as the relative distance of the matching points in the left and right eye images, ie the pixels in the left and right images are found to correspond to the same scene point. For example, if the horizontal coordinate of a point in the image for the left eye is x, and the horizontal coordinate of its corresponding point in the image for the right eye is x', then the disparity d = x' - x.

In one embodiment of estimating disparity, initially a stereo pair of images is acquired. Computing the disparity cost function includes computing a pixel matching cost function 132 and computing a smoothing cost function 134 . A low-cost stereo matching optimization (eg, dynamic programming function 138) is performed to obtain an initial determination of stereo matching the two images. The results of the low-cost optimization are then used to initialize the belief propagation function 136 in order to speed up the belief propagation function to minimize the disparity cost function. It is to be understood that other methods for disparity estimation are known in the art and may be employed by the systems and methods of the present disclosure.

In step 206, a disparity transformation is determined. There are basically two types of parallax transitions: potentially abrupt parallax transitions between film fragments (eg, scenes, shots, etc.), and generally continuous parallax transitions within film fragments (eg, scenes, shots, etc.). As discussed below, a segment means a sequence of frames containing the same content.

Parallax transitions between clips are often discontinuous and abrupt. So to measure disparity transformation, first estimate the disparity map of the last frame of the previous segment and the start frame of the current segment. In other words, assuming that the disparity map at the end of the i-th segment is D _i , and the disparity map at the beginning of the (i+1)-th segment is D _i+1 , then the disparity difference is

δD＝D _i+1 -D _i (1)

To measure the magnitude of the depth change, use the absolute parallax difference

|δD|＝|D _i+1 -D _i | (2)

To get the overall disparity change, the maximum disparity transformation is used, which is

Or use the average disparity transformation, which is

where W and H are the width and height of the disparity map.

Parallax transitions are usually continuous for frames in a clip, but large parallax transitions in a small amount of time will also contribute to viewer eye fatigue. Similar to the disparity change between segments, the disparity difference can be used as a measure, ie, δD=D _i+1 −D _i . However, this measurement will be performed every frame and not just at segment boundaries. Here, the average disparity value over pixels within a frame is determined instead of over pixels across frames, and then the difference between each successive frame is calculated.

Eye strain caused by large parallax and/or parallax changes. Therefore, at step 208, eye strain is estimated based on the disparity map and the disparity transformation. The systems and methods of the present disclosure utilize a very rough model of eyestrain. The system and method assumes that there is a function relating eye fatigue to disparity and disparity change at each frame, and that eye fatigue is accumulated across frames, but decays exponentially over time.

First, assume that there is an "instant eyestrain function" It compares eye strain caused by parallax with average parallax and parallax transformation relevant. Then, if the disparity remains zero after the i-th frame, the eye strain measurement can be expressed as an attenuation model as follows

in is a function that models the immediate effect of parallax on eye fatigue. λ is the attenuation coefficient. The model assumes that if there is no longer parallax on the screen (ie, the point of convergence comes into focus), eyestrain will fade out quickly. Note: Because there may be sudden changes in disparity between fragments, the function It may be different for frames within a fragment and between fragments, which is why they are handled differently above. function A simple example could be with The linear combination between is as follows:

where a and b are weight coefficients which should be different for disparity transformation within a fragment and for disparity transformation between fragments. The values of a and b can be determined empirically.

As the disparity keeps changing across frames, then eye strain should build up over time. However, eye strain cannot rise forever, so a function can be used to model the fading effect of eye strain over time. The S function is used to model the saturation of eye fatigue as follows:

S(ES)＝1/(1+exp(-ES)) (7)

The shape of this function is shown in FIG. 6 .

Given these elements, the overall eye strain measure at frame i can be recursively defined as follows:

where ES _i (t _i ) is the eye strain measurement at frame _i , and ti is the time of frame i, and λ is a constant used to control the decay rate. Calculation of this measurement can be achieved by simulation over time.

Figure 7 is a graphical representation of eye strain measurement equations over time. The eyestrain at frame (i-t) is determined, and an attenuation factor of exp(-λt) is applied to the eyestrain measure. The result is then combined with the instant eye fatigue function for frame i. Apply a sigmoid function to the combined results to determine eye strain at frame i.

Referring to Figure 8, an instant eyestrain function and an overall eyestrain measure are illustrated. The curve at each frame (eg, frame 1, 2, etc.) is the instant eyestrain function for that frame, and the curve at the measurement points is the accumulation of the instant eyestrain function. Referring again to FIG. 5, at step 210, it is determined whether the overall eye strain experienced by the viewer is acceptable. In one embodiment, the overall eye strain measurement is visualized as a graph for operators (eg, directors and editors) to determine from the graph whether eye strain is too high. In another embodiment, the overall eye strain measurement may be compared to a predetermined threshold in order to determine whether correction is required. For example, a curve representing a measure of overall eye strain is generated, and the value of each point on the curve is compared to a predetermined threshold. In this embodiment, the predetermined threshold will be different for different types of scenes and movies.

If eye strain is determined to be too high, then at step 212 a parallax correction or grading will be performed on the stereoscopic images to reduce eye strain. Blending is the process of smoothing disparity values across frames. By smoothing the disparity across frames, sudden changes in disparity can be reduced, and thus eye fatigue can be reduced. One exemplary method for reducing parallax is called convergence adjustment, which is achieved by shifting the right-eye image left or right to adjust the point of convergence. By shifting the right-eye image to the left or right, the parallax of pixels can be artificially reduced or increased, resulting in smaller or greater overall depth, respectively.

The problem with image shifting is that the depth of all pixels is increased by the same amount, independent of the 3D scene geometry. However, if an accurate depth map is available, it is possible to synthesize new views of the scene with new virtual camera positions in order to reduce parallax. In this embodiment, each of the above-determined The disparity value d of a scene point is converted into a depth value z, (ie, the distance from the scene point to the camera). A depth value for each of at least one image (eg, a left-eye view image) is stored in a depth map. The depth values of the depth map are changed accordingly in order to synthesize new views while reducing image parallax. For example, to create a new view, first change the depth value, then redraw the new left or right (or both) image. The repainting process takes a left (or right) image and a depth map, and creates a new right (or left) image. Depth values are 3D information for pixels, so techniques such as ray tracing can be used in order to draw 3D points as 2D pixels in the new view. The new view will have less parallax or less parallax transition and thus will result in reduced eyestrain for the viewer or viewer.

Referring now to FIG. 4 , corresponding images and associated depth maps are stored, eg, in storage device 124 , and can be retrieved for 3D playback. Furthermore, all corrected images of a motion picture or video clip may be stored with associated depth maps in a single digital file 130 representing a stereoscopic version of the motion picture or clip. Digital file 130 may be stored on storage device 124 for later retrieval, for example, for developing a stereoscopic version of the original film.

Although embodiments that incorporate the teachings of the present disclosure have been shown and described in detail herein, those skilled in the art can readily devise any other varied embodiments that still incorporate these teachings. Having described a preferred embodiment of a system and method for measuring potential eye strain experienced while viewing a 3D presentation (which is intended to be illustrative and not limiting), it is noted that those skilled in the art in light of the above teachings Modifications and variations are possible. It is therefore to be understood that changes may be made in the particular embodiments of the disclosure disclosed which are within the scope of the disclosure as outlined by the appended claims.

Claims (22)

1. the method for potential eye fatigue of one kind measurement when viewing three-dimensional (3D) is presented, methods described include：

The first image and the second image (202) are obtained from the first fragment；

Estimate the parallax (204) of at least one corresponding points at least one point and the second image in the first image；

Estimate the parallax conversion (206) of the sequence of the first and second images；And

The parallax conversion of sequence based on parallax and the first and second images determines that the potential eyes when watching 3D and presenting are tired Labor (208)；

Wherein the first image and the second image produce the three-dimensional stereo pairs presented.

2. the method as described in claim 1, wherein estimating disparity switch process (206) also include：

The parallax of the last frame of fragment before estimation；

Estimate the parallax of the first frame of the first fragment；And

It is determined that the difference between the parallax of the parallax of the last frame of fragment and the first frame of the first fragment before.

3. the method as described in claim 1, wherein estimating disparity switch process (206) also include：

Estimate the parallax in each frame of multiple frames of the first fragment；And

Determine the difference between the parallax of each frame of the first fragment.

4. the method as described in claim 1, wherein determining that potential eye fatigue step (208) also includes determining to be used for the first He The instant eye fatigue function of each frame of the sequence of second image.

5. method as claimed in claim 4, wherein determining that potential eye fatigue step (208) is also included decay factor application To the instant eye fatigue function of each frame of the sequence for the first and second images.

6. method as claimed in claim 5, wherein determining that potential eye fatigue step (208) is additionally included in predetermined time period The instant eye fatigue function of each frame of the sequence for the first and second images after upper accumulation decay.

7. method as claimed in claim 6, wherein determining that potential eye fatigue step (208) also includes making first and second The eye fatigue function saturation accumulated in the sequence of image.

8. the method as described in claim 1, in addition to：

Determine whether potential eye fatigue is acceptable (210)；And

If potential eye fatigue is unacceptable, the parallax (212) of the first and second images is corrected.

9. method as claimed in claim 8, wherein aligning step (212) also include at least the one of the first and second images of skew It is individual, to adjust convergent point of the eyes of beholder relative to the first and second images.

10. method as claimed in claim 8, wherein aligning step (212) also have what is reduced including the first fragment of synthesis The new view of parallax.

11. one kind is used for the system (100) for measuring the potential eye fatigue when viewing three-dimensional (3D) is presented, the system bag Include：

For obtaining the part of the first image and the second image from the first fragment；

Disparity estimator (116), for estimate the first image at least one point with it is at least one corresponding in the second image The parallax of point；

Parallax conversion estimator (118), the parallax conversion of the sequence for estimating the first and second images；And

Eye fatigue estimator (120), the parallax conversion for the sequence based on parallax and the first and second images determine Watch potential eye fatigue when 3D is presented；

Wherein the first image and the second image produce the three-dimensional stereo pairs presented.

12. system (100) as claimed in claim 11, wherein parallax conversion estimator (118) operation are come fragment before estimating Last frame parallax, estimate the parallax of the first frame of the first fragment, and before determining the last frame of fragment parallax and the Difference between the parallax of first frame of one fragment.

13. system (100) as claimed in claim 11, wherein parallax conversion estimator (118) are operated to estimate the first fragment Multiple frames each frame in parallax, and determine the first fragment each frame parallax between difference.

14. system (100) as claimed in claim 11, wherein eye fatigue estimator (120) are operated to determine to be used for first With the instant eye fatigue function of each frame of the sequence of the second image.

15. the operation of system (100) as claimed in claim 14, wherein eye fatigue estimator (120) should by decay factor Use the instant eye fatigue function of each frame of the sequence for the first and second images.

16. the operation of system (100) as claimed in claim 15, wherein eye fatigue estimator (120) came in the predetermined time The instant eye fatigue function of each frame of the sequence for the first and second images in section after accumulation decay.

17. system (100) as claimed in claim 16, wherein eye fatigue estimator (120) operation makes first and the The eye fatigue function saturation accumulated in the sequence of two images.

18. system (100) as claimed in claim 11, in addition to parallax offset mechanism (122), if eye fatigue estimator (120) determine that potential eye fatigue is unacceptable, then parallax offset mechanism (122) is operated to correct regarding for the first and second images Difference.

19. system (100) as claimed in claim 18, wherein parallax offset mechanism (122) are operated to offset the first and second figures Picture it is at least one, to adjust convergent point of the eyes of beholder relative to the first and second images.

20. system (100) as claimed in claim 18, wherein parallax offset mechanism (122) are operated to synthesize the tool of the first fragment There is the new view of the parallax of reduction.

21. a kind of program storage device that can be read by machine, described program storage device, which positively embodies, to be performed by machine , the program of the instruction of method and step for performing to measure the potential eye fatigue when viewing three-dimensional (3D) is presented, Methods described includes：

The first image and the second image (202) are obtained from the first fragment；

Estimate the parallax (204) of at least one corresponding points at least one point and the second image in the first image；

Estimate the parallax conversion (206) of the sequence of the first and second images；And

The parallax conversion of sequence based on parallax and the first and second images determines that the potential eyes when watching 3D and presenting are tired Labor (208)；

Wherein the first image and the second image produce the three-dimensional stereo pairs presented.

22. program storage device as claimed in claim 21, wherein methods described also include：

Determine whether potential eye fatigue is acceptable (210)；And

If potential eye fatigue is unacceptable, the parallax (212) of the first and second images is corrected.