Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/67387
Citations
Scopus Web of Science® Altmetric
?
?
Type: Conference paper
Title: Improved human detection and classification in thermal images
Author: Wang, W.
Zhang, J.
Shen, C.
Citation: Proceedings of IEEE 17th International Conference on Image Processing (ICIP 2010), 26-29th September, 2010;. pp.2313-2316
Publisher: IEEE
Publisher Place: Hong Kong
Issue Date: 2010
Conference Name: IEEE International Conference on Image Processing (ICIP) (17th : 2010 : Hong Kong)
Statement of
Responsibility: 
Weihong Wang, Jian Zhang and Chunhua Shen
Abstract: We present a new method for detecting pedestrians in thermal images. The method is based on the Shape Context Descriptor (SCD) with the Adaboost cascade classifier framework. Compared with standard optical images, thermal imaging cameras offer a clear advantage for night-time video surveillance. It is robust on the light changes in day-time. Experiments show that shape context features with boosting classification provide a significant improvement on human detection in thermal images. In this work, we have also compared our proposed method with rectangle features on the public dataset of thermal imagery. Results show that shape context features are much better than the conventional rectangular features on this task.
Rights: © Copyright 2010 IEEE – All Rights Reserved
RMID: 0020112829
DOI: 10.1109/ICIP.2010.5649946
Appears in Collections:Computer Science publications

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.