Human Action Recognition With Video Data: Research and Evaluation Challenges

Given a video sequence, the task of action recognition is to identify the most similar action among the action sequences learned by the system. Such human action recognition is based on evidence gathered from videos. It has wide application including surveillance, video indexing, biometrics, telehea...

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Bibliographic Details
Published in:IEEE transactions on human-machine systems 2014-10, Vol.44 (5), p.650-663
Main Authors: Ramanathan, Manoj, Wei-Yun Yau, Eam Khwang Teoh
Format: Article
Language:English
Subjects:
Action recognition
anthropometric variations
Anthropometry
camera motion
Cameras
Classification
Clutter
execution rate
Feature extraction
Hidden Markov models
Human
Indexing
Legged locomotion
Recognition
Robustness
Shape
Surveillance
Tasks
Video sequences
view invariance
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Summary:Given a video sequence, the task of action recognition is to identify the most similar action among the action sequences learned by the system. Such human action recognition is based on evidence gathered from videos. It has wide application including surveillance, video indexing, biometrics, telehealth, and human-computer interaction. Vision-based human action recognition is affected by several challenges due to view changes, occlusion, variation in execution rate, anthropometry, camera motion, and background clutter. In this survey, we provide an overview of the existing methods based on their ability to handle these challenges as well as how these methods can be generalized and their ability to detect abnormal actions. Such systematic classification will help researchers to identify the suitable methods available to address each of the challenges faced and their limitations. In addition, we also identify the publicly available datasets and the challenges posed by them. From this survey, we draw conclusions regarding how well a challenge has been solved, and we identify potential research areas that require further work.
ISSN:2168-2291
2168-2305
DOI:10.1109/THMS.2014.2325871