Rule-based approach for enhancing the motion trajectories in human activity recognition
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Date
2010
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Journal Title
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Type
Conference Paper
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Proceedings of the 2010 10th International Conference on Intelligent Systems Design and Applications, ISDA'10
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Abstract
In this paper, we propose a rule-based system for semantically understanding and analyzing the motion of the trajectories of the human activity. The proposed system can be used as a preprocessing phase for enhancing the object detection process. Detected trajectories are classified into three categories; normal, semi-normal and abnormal trajectories according to the distances between their adjacent points. Abnormal trajectories are removed from the trajectory space. Semi-normal trajectories are broken into small normal trajectories that are linked later to form a longer normal trajectory. The proposed system does not assume a specific trajectory length and hence is more generic than similar trajectory enhancement approaches. The effectiveness of the proposed approach is demonstrated through several experimental results using known human motion datasets. � 2010 IEEE.
Description
Scopus
Keywords
Action recognition, Human activity recognition, Motion trajectory, SIFT algorithm, Visual surviellance system, Action recognition, Human activity recognition, Motion trajectories, SIFT algorithm, Visual surviellance system, Algorithms, Image recognition, Intelligent systems, Systems analysis, Trajectories