@inproceedings{cdc0dd904ff044689969a760c7a76d48,
title = "Representing discrimination of video by a motion map",
abstract = "Representing the content of the video by a motion map is a challenging problem in video analysis. This paper proposes to integrate the discriminative information of a video into a map by optimizing the recognition accuracy of the original video in the action recognition task. The motion map represents a prefix of video frames sequence. A motion map and the next video frame can be integrated to a new motion map by the proposed 3-dimensional convolution based model. This model can be trained by incremental length clips from training videos iteratively, and the final acquired network can be used for generating the motion map of the whole video. Experimental results on the UCF101 and the HMDB51 datasets show that our method achieves better results compared with other related methods.",
keywords = "Action recognition, CNN, Discriminative information, Video analysis, Video-to-Image",
author = "Wennan Yu and Yuchao Sun and Feiwu Yu and Xinxiao Wu",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG, part of Springer Nature 2018.; 18th Pacific-Rim Conference on Multimedia, PCM 2017 ; Conference date: 28-09-2017 Through 29-09-2017",
year = "2018",
doi = "10.1007/978-3-319-77380-3_67",
language = "English",
isbn = "9783319773797",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "703--711",
editor = "Bing Zeng and Hongliang Li and {El Saddik}, Abdulmotaleb and Xiaopeng Fan and Shuqiang Jiang and Qingming Huang",
booktitle = "Advances in Multimedia Information Processing – PCM 2017 - 18th Pacific-Rim Conference on Multimedia, Revised Selected Papers",
address = "Germany",
}