SG11201909651VA - Time domain motion detection method and system, electronic device and computer storage medium - Google Patents

Time domain motion detection method and system, electronic device and computer storage medium

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Publication number
SG11201909651VA
SG11201909651VA SG11201909651VA SG11201909651VA SG 11201909651V A SG11201909651V A SG 11201909651VA SG 11201909651V A SG11201909651V A SG 11201909651VA SG 11201909651V A SG11201909651V A SG 11201909651VA
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Singapore
Prior art keywords
time domain
action
segment
computer storage
interval
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Inventor
Xiaoou Tang
Yuanjun Xiong
Yue Zhao
Limin Wang
Zhirong Wu
Dahua Lin
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Beijing Sensetime Technology Development Co Ltd
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Application filed by Beijing Sensetime Technology Development Co Ltd filed Critical Beijing Sensetime Technology Development Co Ltd
Publication of SG11201909651VA publication Critical patent/SG11201909651VA/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content
    • G06V20/46—Extracting features or characteristics from the video content, e.g. video fingerprints, representative shots or key frames
    • G06V20/47—Detecting features for summarising video content
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/20—Analysis of motion
    • G06T7/269—Analysis of motion using gradient-based methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • G06V10/443—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by matching or filtering
    • G06V10/449—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters
    • G06V10/451—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters with interaction between the filter responses, e.g. cortical complex cells
    • G06V10/454—Integrating the filters into a hierarchical structure, e.g. convolutional neural networks [CNN]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content
    • G06V20/44—Event detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content
    • G06V20/46—Extracting features or characteristics from the video content, e.g. video fingerprints, representative shots or key frames
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/40—Scenes; Scene-specific elements in video content
    • G06V20/49—Segmenting video sequences, i.e. computational techniques such as parsing or cutting the sequence, low-level clustering or determining units such as shots or scenes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/20—Movements or behaviour, e.g. gesture recognition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/217—Validation; Performance evaluation; Active pattern learning techniques
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/048—Activation functions
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Evolutionary Computation (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Computing Systems (AREA)
  • Molecular Biology (AREA)
  • Software Systems (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Biomedical Technology (AREA)
  • Data Mining & Analysis (AREA)
  • General Engineering & Computer Science (AREA)
  • Biophysics (AREA)
  • Computational Linguistics (AREA)
  • Mathematical Physics (AREA)
  • Social Psychology (AREA)
  • Psychiatry (AREA)
  • Human Computer Interaction (AREA)
  • Databases & Information Systems (AREA)
  • Medical Informatics (AREA)
  • Biodiversity & Conservation Biology (AREA)
  • Image Analysis (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • Two-Way Televisions, Distribution Of Moving Picture Or The Like (AREA)
  • Television Signal Processing For Recording (AREA)

Abstract

TIME DOMAIN ACTION DETECTING METHOD AND SYSTEM, ELECTRONIC DEVICE, AND COMPUTER STORAGE MEDI UM T ime domain action detecting methods and systems, ele ctronic devices, and computer storage medi um are provided. The method includes : obtaining a time domain interval in a video with an action instance and at least one adjacent segment in the time domain interval ; separately extracting action features of at l east two video segment s in candidate segment s, where the candidate segment s comprises video segment corresponding to the time domain interval and adjacent segment s thereof; pooling the action features of the at least two video segment s in the candidate seg ment s, to obtain a global feature of the segment corresponding to the time interval ; determining, based on the global feature, an action integrity score of the video segment corresponding to the time domain interval . The embodiments of the present disclosure benefit accurate ly determining whether a time interval comprises integral instance, improve the accuracy of action integrity identification . [ FIG . 1 ]
SG11201909651V 2017-04-20 2018-04-20 Time domain motion detection method and system, electronic device and computer storage medium SG11201909651VA (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201710263004.2A CN108229280B (en) 2017-04-20 2017-04-20 Time domain action detection method and system, electronic equipment and computer storage medium
PCT/CN2018/083924 WO2018192570A1 (en) 2017-04-20 2018-04-20 Time domain motion detection method and system, electronic device and computer storage medium

Publications (1)

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SG11201909651VA true SG11201909651VA (en) 2019-11-28

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US (1) US10915741B2 (en)
CN (1) CN108229280B (en)
SG (1) SG11201909651VA (en)
WO (1) WO2018192570A1 (en)

Families Citing this family (25)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108615011B (en) * 2018-04-24 2021-10-08 东南大学 Non-pruning video behavior identification and prediction method based on multi-scale sliding window
CN109325440B (en) * 2018-09-19 2021-04-30 深圳市赢世体育科技有限公司 Human body action recognition method and system
CN110955800A (en) * 2018-09-26 2020-04-03 传线网络科技（上海）有限公司 Video retrieval method and device
US11636681B2 (en) * 2018-11-21 2023-04-25 Meta Platforms, Inc. Anticipating future video based on present video
CN111275373B (en) * 2018-12-05 2024-05-21 北京京东乾石科技有限公司 Efficiency acquisition method, system and equipment of elevator and readable storage medium
CN111385490B (en) * 2018-12-28 2021-07-13 清华大学 Video splicing method and device
CN111382306B (en) * 2018-12-28 2023-12-01 杭州海康威视数字技术股份有限公司 Method and device for inquiring video frame
CN110263641A (en) * 2019-05-17 2019-09-20 成都旷视金智科技有限公司 Fatigue detection method, device and readable storage medium storing program for executing
CN110110812B (en) * 2019-05-20 2022-08-19 江西理工大学 Stream depth network model construction method for video motion recognition
CN110188878A (en) * 2019-05-31 2019-08-30 北京市商汤科技开发有限公司 Neural network searching method and device
CN110263733B (en) * 2019-06-24 2021-07-23 上海商汤智能科技有限公司 Image processing method, nomination evaluation method and related device
CN110543830B (en) * 2019-08-12 2022-05-13 珠海格力电器股份有限公司 Motion detection method, motion detection device, and storage medium
CN110516636A (en) * 2019-08-30 2019-11-29 盈盛智创科技(广州)有限公司 A kind of monitoring method of process, device, computer equipment and storage medium
CN110688927B (en) * 2019-09-20 2022-09-30 湖南大学 Video action detection method based on time sequence convolution modeling
CN110659624A (en) * 2019-09-29 2020-01-07 上海依图网络科技有限公司 Group personnel behavior identification method and device and computer storage medium
CN111046736B (en) * 2019-11-14 2021-04-16 北京房江湖科技有限公司 Method, device and storage medium for extracting text information
US11138441B2 (en) * 2019-12-06 2021-10-05 Baidu Usa Llc Video action segmentation by mixed temporal domain adaption
CN111222476B (en) * 2020-01-10 2023-06-06 北京百度网讯科技有限公司 Video time sequence action detection method and device, electronic equipment and storage medium
CN111291631B (en) * 2020-01-17 2023-11-07 北京市商汤科技开发有限公司 Video analysis method and related model training method, device and apparatus thereof
CN113810751B (en) * 2020-06-12 2022-10-28 阿里巴巴集团控股有限公司 Video processing method and device, electronic device and server
CN116635911A (en) * 2020-07-16 2023-08-22 Oppo广东移动通信有限公司 Action recognition method and related device, storage medium
CN112380394B (en) 2020-10-27 2022-05-10 浙江工商大学 Progressive positioning method for positioning from text to video clip
CN112464898A (en) * 2020-12-15 2021-03-09 北京市商汤科技开发有限公司 Event detection method and device, electronic equipment and storage medium
US20230281245A1 (en) * 2022-03-07 2023-09-07 Twelve Labs, Inc. Video retrieval method and apparatus using post processing on segmented videos
CN115830489B (en) * 2022-11-03 2023-10-20 南京小网科技有限责任公司 Intelligent dynamic analysis system based on ai identification

Family Cites Families (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9147129B2 (en) * 2011-11-18 2015-09-29 Honeywell International Inc. Score fusion and training data recycling for video classification
CN104933436B (en) * 2014-03-19 2018-09-14 通用汽车环球科技运作有限责任公司 The multi-cam factory monitoring of view-based access control model with the scoring of dynamic integrality
US10572735B2 (en) * 2015-03-31 2020-02-25 Beijing Shunyuan Kaihua Technology Limited Detect sports video highlights for mobile computing devices
CN104933417B (en) * 2015-06-26 2019-03-15 苏州大学 A kind of Activity recognition method based on sparse space-time characteristic
CN105354528A (en) * 2015-07-15 2016-02-24 中国科学院深圳先进技术研究院 Depth image sequence based human body action identification method and system
US10068138B2 (en) * 2015-09-17 2018-09-04 Canon Kabushiki Kaisha Devices, systems, and methods for generating a temporal-adaptive representation for video-event classification
CN105740833B (en) * 2016-02-03 2019-03-22 北京工业大学 A kind of Human bodys' response method based on depth sequence
CN106203255B (en) * 2016-06-24 2019-04-23 华中科技大学 A kind of pedestrian based on time unifying recognition methods and system again
CN106203283A (en) * 2016-06-30 2016-12-07 重庆理工大学 Based on Three dimensional convolution deep neural network and the action identification method of deep video
CN106897714B (en) * 2017-03-23 2020-01-14 北京大学深圳研究生院 Video motion detection method based on convolutional neural network

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WO2018192570A1 (en) 2018-10-25
CN108229280B (en) 2020-11-13
CN108229280A (en) 2018-06-29
US10915741B2 (en) 2021-02-09
US20190138798A1 (en) 2019-05-09

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