Abstract
Inspired by the binary-based descriptors (e.g. LBP, ALOHA, FREAK, BRISK), we propose the 3D Binary Pair Differences (3DBPD) video descriptor for action recognition. By comparing several spatio-temporal sub-regions around interests points, our descriptor is a feature vector with a dimensionality of up to 30% smaller than that of existing state-of-the-art descriptors. We demonstrate the effectiveness of the 3DBPD descriptor for action recognition with a SVM classifier and a simple Bag Of Video Words (BOV) generated using k-means. The proposed descriptor has very competitive recognition rates compared to other state-of-the-art descriptors, with an outstanding performance in terms of speed. Additionally, the 3DBPD descriptor requires a small codebook compared to those required by existing BOV-based descriptors.
Original language | English |
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Title of host publication | 2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings |
Place of Publication | United States |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 4185-4189 |
Number of pages | 5 |
ISBN (Print) | 9781467399616 |
DOIs | |
Publication status | Published - 2016 |
Event | 2016 23rd IEEE International Conference on Image Processing: ICIP 2016 - Phoenix Convention Center, Phoenix, United States Duration: 25 Sep 2016 → 28 Sep 2016 Conference number: 125190 http://2016.ieeeicip.org/default.asp |
Conference
Conference | 2016 23rd IEEE International Conference on Image Processing |
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Country | United States |
City | Phoenix |
Period | 25/09/16 → 28/09/16 |
Internet address |