A survey on vision-based human action recognition
Image and Vision Computing
Modelling postures of human movements
CIARP'10 Proceedings of the 15th Iberoamerican congress conference on Progress in pattern recognition, image analysis, computer vision, and applications
A semantic-based probabilistic approach for real-time video event recognition
Computer Vision and Image Understanding
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In this study a new approach is presented for the recognition of human actions of everyday life with a fixed camera. The originality of the presented method consists in characterizing sequences by a temporal succession of semi-global features, which are extracted from “space-time micro-volumes”. The advantage of this approach lies in the use of robust features (estimated on several frames) associated with the ability to manage actions with variable durations and easily segment the sequences with algorithms that are specific to time-varying data. Each action is actually characterized by a temporal sequence that constitutes the input of a Hidden Markov Model system for the recognition. Results presented of 1,614 sequences performed by several persons validate the proposed approach.