Abstract
In this paper, an effective top-view people detection algorithm based on multiple subarea models is proposed for smart home system. Conventional single model based detector is difficult to achieve high performance in top-view people detection since there are too many possible individual poses in the top-view based image scene and it is impossible to cover all the poses with single model. Therefore, this paper develops a model of 9 typical poses to mitigate the low detection performance problem of conventional method. Moreover, by restricting the local scope of every pose model, the proposed approach yields an improved detection rate while reducing false alarm compared to the conventional single model based detector.
Original language | English |
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Title of host publication | 2016 IEEE International Conference on Consumer Electronics, ICCE 2016 |
Editors | Francisco J. Bellido, Daniel Diaz-Sanchez, Nicholas C. H. Vun, Carsten Dolar, Wing-Kuen Ling |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 1-2 |
Number of pages | 2 |
ISBN (Electronic) | 9781467383646 |
DOIs | |
Publication status | Published - 2016 Mar 10 |
Event | IEEE International Conference on Consumer Electronics, ICCE 2016 - Las Vegas, United States Duration: 2016 Jan 7 → 2016 Jan 11 |
Publication series
Name | 2016 IEEE International Conference on Consumer Electronics, ICCE 2016 |
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Other
Other | IEEE International Conference on Consumer Electronics, ICCE 2016 |
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Country/Territory | United States |
City | Las Vegas |
Period | 16/1/7 → 16/1/11 |
Bibliographical note
Publisher Copyright:© 2016 IEEE.
ASJC Scopus subject areas
- Computer Networks and Communications
- Electrical and Electronic Engineering