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Localizing volumetric motion for action recognition in realistic videos
2009
Proceedings of the seventeen ACM international conference on Multimedia - MM '09
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This paper presents a novel motion localization approach for recognizing actions and events in real videos. Examples include StandUp and Kiss in Hollywood movies. ...
Figure 1: Examples of realistic human actions in Hollywood movies and KungFu videos. Actions in real videos exhibit large visual variation. ...
CONCLUSIONS AND FUTURE WORKS We have presented a novel motion localization approach for realistic action recognition. ...
doi:10.1145/1631272.1631342
dblp:conf/mm/WuNLZ09
fatcat:fxnhowv4urbwhc3vlqkhuuhnwq
Action Recognition Using Volumetric Motion Representations
[article]
2019
arXiv
pre-print
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In this work, we introduce a novel representation of motion as a voxelized 3D vector field and demonstrate how it can be used to improve performance of action recognition networks. ...
Both the construction of this representation from RGB-D video and inference can be run in real time. ...
Following on the success of 3D CNNs for the object recognition domain in [26] , we investigate its application towards action recognition by using a volumetric motion field. ...
arXiv:1911.08511v1
fatcat:eeetdkc5bzad7or2am2f6cldba
Action bank: A high-level representation of activity in video
2012
2012 IEEE Conference on Computer Vision and Pattern Recognition
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Activity recognition in video is dominated by low-and mid-level features, and while demonstrably capable, by nature, these features carry little semantic meaning. ...
We have tested action bank on four major activity recognition benchmarks. ...
Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright annotation thereon. ...
doi:10.1109/cvpr.2012.6247806
dblp:conf/cvpr/SadanandC12
fatcat:zi76zfmbn5ga7b72a5eh46ozlu
Interest Point Selection with Spatio-temporal Context for Realistic Action Recognition
2012
2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance
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One reason of the low performance is that the STIPs only reflect the local change in videos, which is not enough to obtain stable informative features for action representation in realistic scene. ...
Spatio-Temporal Interest Point (STIP) has been widely used for human action recognition. ...
In this paper, we propose an approach to select the stable STIPs for action recognition in realistic scene. ...
doi:10.1109/avss.2012.43
dblp:conf/avss/ShanZZHWH12
fatcat:btb6b66yjfglbhbntxe5pjs46a
Volumetric spatial feature representation for view-invariant human action recognition using a depth camera
2015
Optical Engineering: The Journal of SPIE
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In this paper, we propose a volumetric spatial feature representation (VSFR) that measures the density of 3-D point clouds for view-invariant human action recognition from depth sequence images. ...
The problem of viewpoint variations is a challenging issue in vision-based human action recognition. ...
Temporal Action Descriptor For detecting temporal motion characteristics, we use an SSM that can graphically represent temporal features in a sequence of images and extract a local descriptor for each ...
doi:10.1117/1.oe.54.3.033102
fatcat:ug4i62vinfdl5movqjyyhbskwy
Space-Time Shapelets for Action Recognition
2008
2008 IEEE Workshop on Motion and video Computing
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local motion patterns formed by the actions. ...
Recent works in action recognition have begun to treat actions as space-time volumes. ...
Conclusions We looked at the problem of action recognition as that of spatio-temporal volumetric matching. ...
doi:10.1109/wmvc.2008.4544051
fatcat:eu7ybzduhjg3ddmyfgi3rlge3i
Spatiotemporal Deformable Part Models for Action Detection
2013
2013 IEEE Conference on Computer Vision and Pattern Recognition
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Extensive experiments on several video datasets demonstrate the strength of spatiotemporal DPMs for classifying and localizing actions. ...
This paper explores the generalization of deformable part models from 2D images to 3D spatiotemporal volumes to better study their effectiveness for action detection in video. ...
Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright annotation thereon. ...
doi:10.1109/cvpr.2013.341
dblp:conf/cvpr/TianSS13
fatcat:u5scvt4nnbfzvgnkz76iiuw7ge
Egocentric Activity Recognition and Localization on a 3D Map
[article]
2022
arXiv
pre-print
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Our method demonstrates strong results on both action recognition and 3D action localization across seen and unseen environments. ...
Our model takes the inputs of a Hierarchical Volumetric Representation (HVR) of the 3D environment and an egocentric video, infers the 3D action location as a latent variable, and recognizes the action ...
Portions of this project were supported in part by a gift from Facebook. ...
arXiv:2105.09544v3
fatcat:rrwg6yk4f5d4joa6kkhvjfllde
Action Recognition in Videos: from Motion Capture Labs to the Web
[article]
2010
arXiv
pre-print
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We propose an organizing framework which puts in evidence the evolution of the area, with techniques moving from heavily constrained motion capture scenarios towards more challenging, realistic, "in the ...
This paper presents a survey of human action recognition approaches based on visual data recorded from a single video camera. ...
Ivan Laptev for his comments on earlier versions of this manuscript, as well as the Brazilian funding agencies CAPES, CNPq and FAPEMIG. ...
arXiv:1006.3506v1
fatcat:rti7aqnwxfgwdivslh2c7w2wly
Advances in Human Action Recognition: A Survey
[article]
2015
arXiv
pre-print
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Human action recognition has been an important topic in computer vision due to its many applications such as video surveillance, human machine interaction and video retrieval. ...
This survey gives an overview of the most recent advances in human action recognition during the past several years, following a well-formed taxonomy proposed by a previous survey. ...
Action Recognition with Space-Time Local Features The application of local features in action recognition was extended from object recognition in images. ...
arXiv:1501.05964v1
fatcat:tdkrneqvifdf5ppg3dmbrvy43a
A Study of Vision based Human Motion Recognition and Analysis
2016
International Journal of Ambient Computing and Intelligence (IJACI)
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2016 pre-print arXiv:1608.06761v1 fatcat:y36jyqu25bewxa3svmgbutrtd4
A bird's eye view for new researchers in the domain is presented in the paper. ...
The human motion recognition domain has been active for more than two decades, and has provided a large amount of literature. ...
It is more realistic and contains videos captured with surveillance cameras in indoor and outdoor scenes. ...
doi:10.4018/ijaci.2016070104
fatcat:doyiyb2fizh75dntg6kvmqoqey
TechWare: Video-Based Human Action Detection Resources [Best of the Web
2010
IEEE Signal Processing Magazine
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STIP features have been frequently used for action recognition. ...
In the early days, human bodies were tracked and segmented from the videos to characterize actions and motion trajectories are popularly used to represent and recognize actions. ...
For action recognition, each video clip contains only one action and the task is to classify which type of action it exhibits. ...
doi:10.1109/msp.2010.937496
fatcat:56rypucynneohale67doue3avy
Localized Multiple Kernel Learning for Realistic Human Action Recognition in Videos
2011
IEEE transactions on circuits and systems for video technology (Print)
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Realistic human action recognition in videos has been a useful yet challenging task. ...
Video shots of same actions may present huge intra-class variations in terms of visual appearance, kinetic patterns, video shooting, and editing styles. ...
This paper focuses on realistic human action recognition in unconstrained movie and web videos. The difficulties of realistic action recognition lie mainly in two facts. ...
doi:10.1109/tcsvt.2011.2130230
fatcat:cl74p2jjorcifbyvf44u6axhku
Spatio-temporal action localization for human action recognition in large dataset
2015
Video Surveillance and Transportation Imaging Applications 2015
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Human action recognition has drawn much attention in the field of video analysis. ...
In this paper, we develop a human action detection and recognition process based on the tracking of Interest Points (IP) trajectory. ...
However, in, 46 authors investigate architectures of indiscriminately trained deep Convolutional Networks (ConvNets) for action recognition in video. ...
doi:10.1117/12.2082880
fatcat:5n662thu5bda5b3d4zcuasn6xm
Human action detection via boosted local motion histograms
2008
Machine Vision and Applications
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This paper presents a novel learning method for human action detection in video sequences. ...
To develop effective representation while remaining resistant to background motions, only motion information is exploited to define suitable descriptors for action volumes. ...
Many previous approaches for behavior recognition were based on tracking models [17, 19, 22] , which apply tracked motion trajectories of body parts to action recognition. ...
doi:10.1007/s00138-008-0168-5
fatcat:yp5guppgpvflnj7shgfnv2u3xe
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