Results 11 to 20 of about 461,436 (263)
Proceedings of the AAAI Conference on Artificial Intelligence, 2021 Recognition in planning seeks to find agent intentions, goals or activities given a set of observations and a knowledge library (e.g. goal states, plans or domain theories). In this work we introduce the problem of Online Action Recognition. It consists in recognizing, in an open world, the planning action that best explains a partially observable ...
Suárez Hernández, Alejandro +3 more
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Darwintrees for Action Recognition [PDF]
2017 IEEE International Conference on Computer Vision Workshops (ICCVW), 2017 We propose a novel mid-level representation for action/activity recognition on RGB videos. We model the evolution of improved dense trajectory features not only for the entire video sequence, but also on subparts of the video. Subparts are obtained using a spectral divisive clustering that yields an unordered binary tree decomposing the entire cloud of
Albert Clapés +2 more
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Early Action Recognition with Action Prototypes
CoRR, 2023 Early action recognition is an important and challenging problem that enables the recognition of an action from a partially observed video stream where the activity is potentially unfinished or even not started. In this work, we propose a novel model that learns a prototypical representation of the full action for each class and uses it to regularize ...
Guglielmo Camporese +4 more
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Action recognition in videos [PDF]
2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA), 2012 Applications such as video surveillance, robotics, source selection, and video indexing often require the recognition of actions based on the motion of different actors in a video. Certain applications may require assigning activities to several predefined classes, while others may rely on the detection of abnormal or infrequent activities.
Christian Wolf 0001, Atilla Baskurt
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Action Recognition with Actons [PDF]
2013 IEEE International Conference on Computer Vision, 2013 With the improved accessibility to an exploding amount of video data and growing demands in a wide range of video analysis applications, video-based action recognition/classification becomes an increasingly important task in computer vision. In this paper, we propose a two-layer structure for action recognition to automatically exploit a mid-level ...
Jun Zhu +4 more
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Action Capsules: Human skeleton action recognition
Computer Vision and Image Understanding, 2023 11 pages, 11 ...
Ali Farajzadeh Bavil +2 more
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Kernelized covariance for action recognition [PDF]
2016 23rd International Conference on Pattern Recognition (ICPR), 2016 In this paper we aim at increasing the descriptive power of the covariance matrix, limited in capturing linear mutual dependencies between variables only. We present a rigorous and principled mathematical pipeline to recover the kernel trick for computing the covariance matrix, enhancing it to model more complex, non-linear relationships conveyed by ...
Jacopo Cavazza +3 more
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Instant Action Recognition [PDF]
, 2009 In this paper, we present an efficient system for action recognition from very short sequences. For action recognition typically appearance and/or motion information of an action is analyzed using a large number of frames. This is a limitation if very fast actions (e.g., in sport analysis) have to be analyzed.
Thomas Mauthner +2 more
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Efficient Action Recognition with MoFREAK [PDF]
2013 International Conference on Computer and Robot Vision, 2013 Recent work shows that local binary feature descriptors are effective for increasing the efficiency of object recognition, while retaining comparable performance to other state of the art descriptors. An extension of these approaches to action recognition in videos would facilitate huge gains in efficiency, due to the computational advantage of ...
Chris Whiten +2 more
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Action recognition by dense trajectories [PDF]
CVPR 2011, 2011 Feature trajectories have shown to be efficient for representing videos. Typically, they are extracted using the KLT tracker or matching SIFT descriptors between frames. However, the quality as well as quantity of these trajectories is often not sufficient. Inspired by the recent success of dense sampling in image classification, we propose an approach
Wang, Heng +3 more
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