Publication Details
Human action recognition for real-time applications
Space-time interest points, action recognition, real-time processing, SVM
Action recognition in video is an important part of many applications. While the performance of action recognition has been intensively investigated, not much research so far has been done in the understanding of how long a sequence of video frames is needed to correctly recognize certain actions. This paper presents a new method of measurement of the length of the video sequence necessary to recognize the actions based on space-time feature points. Such length is the key information necessary to successfully recognize the actions in real-time or performance critical applications. The action recognition used in the presented approach is the state-of-the-art one; vocabulary, bag of words and SVM processing. The proposed methods is experimentally evaluated on human action recognition dataset.
@INPROCEEDINGS{FITPUB10501,
author = "Ivo \v{R}ezn\'{i}\v{c}ek and Pavel Zem\v{c}\'{i}k",
title = "Human action recognition for real-time applications",
pages = "646--653",
booktitle = "Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods",
year = 2014,
location = "Angers, FR",
ISBN = "978-989-758-018-5",
language = "english",
url = "https://www.fit.vut.cz/research/publication/10501"
}