Yang et al., 2022 - Google Patents
Design and implementation of intelligent analysis technology in sports video target and trajectory tracking algorithmYang et al., 2022
View PDF- Document ID
- 15369124131624158803
- Author
- Yang X
- Wang H
- Publication year
- Publication venue
- Wireless Communications and Mobile Computing
External Links
Snippet
The object tracking is an important task to future generations to find accurate information from frame (sports or any cctv). The available models like RFO, DT, Xboosting, Gradient boosting, and CNN are outdated for sports video tracking using video. The target and …
- 238000004458 analytical method 0 title abstract description 27
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6267—Classification techniques
- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
- G06K9/00771—Recognising scenes under surveillance, e.g. with Markovian modelling of scene activity
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30781—Information retrieval; Database structures therefor; File system structures therefor of video data
- G06F17/30784—Information retrieval; Database structures therefor; File system structures therefor of video data using features automatically derived from the video content, e.g. descriptors, fingerprints, signatures, genre
- G06F17/30799—Information retrieval; Database structures therefor; File system structures therefor of video data using features automatically derived from the video content, e.g. descriptors, fingerprints, signatures, genre using low-level visual features of the video content
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
- G06K9/00711—Recognising video content, e.g. extracting audiovisual features from movies, extracting representative key-frames, discriminating news vs. sport content
- G06K9/00718—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Pervaiz et al. | Artificial neural network for human object interaction system over Aerial images | |
| Žemgulys et al. | Recognition of basketball referee signals from real-time videos | |
| Zhang et al. | Social attribute-aware force model: exploiting richness of interaction for abnormal crowd detection | |
| Beetz et al. | Aspogamo: Automated sports game analysis models | |
| Jiang et al. | Multiple pedestrian tracking from monocular videos in an interacting multiple model framework | |
| de Almeida et al. | Detection of global and local motion changes in human crowds | |
| Qian et al. | Deep learning assisted robust visual tracking with adaptive particle filtering | |
| Senst et al. | Detecting people carrying objects based on an optical flow motion model | |
| Yang et al. | Design and implementation of intelligent analysis technology in sports video target and trajectory tracking algorithm | |
| Pan | A method of key posture detection and motion recognition in sports based on Deep Learning | |
| Du et al. | Extracting features from foul actions of basketball players in real time using machine vision | |
| CN108256567A (en) | A kind of target identification method and system based on deep learning | |
| Jin | Original Research Article Video analysis and data-driven tactical optimization of sports football matches: Visual recognition and strategy analysis algorithm | |
| Needham | Tracking and modelling of team game interactions | |
| Spagnolo et al. | On-field testing and evaluation of a goal-line technology system | |
| Liu et al. | A Sports Video Behavior Recognition Using Local Spatiotemporal Patterns | |
| Zuo | Visualization of football tactics with deep learning models | |
| Correia et al. | Violence detection in video game metadata using ConvLSTM | |
| Wang et al. | Research and implementation of the sports analysis system based on 3D image technology | |
| He et al. | Research on long jump posture in school physical education teaching based on video analysis | |
| Huang et al. | Error motion tracking method for athletes based on multi eye machine vision | |
| Goyal et al. | Moving object detection in video streaming using improved DNN algorithm | |
| Wu | Sports intelligent assistance system based on deep learning | |
| Zhou et al. | [Retracted] The Application and Development Trend of Youth Sports Simulation Based on Computer Vision | |
| Liu et al. | Design of Sports Competition Assistant Evaluation System Based on Big Data and Action Recognition Algorithm |