Abstract
In a pedestrian detection system, the application of color information can increase the detection rate; however, the detection speed will be slowed down a lot. This paper presents a fast pedestrian detection method using color information. It firstly scans a pair of sequential gray-scale frames to select candidates using both appearance and motion features; and then uses information of each color channel (RGB) to do a further confirmation with support vector machine based classifiers. Compared with pedestrian detection systems that only use gray-scale information, the system using our method has almost the same detection speed; at the same time, it also gets a better detection rate and false-positive rate. The experiment in a pedestrian detection system with a single optical camera proves the effectiveness of our method.
Keywords
- Support Vector Machine
- False Positive Rate
- Support Vector Machine Classifier
- Color Information
- Color Channel
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2006 Springer-Verlag Berlin Heidelberg
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Xu, Y.W., Cao, X.B., Qiao, H., Wang, F.Y. (2006). Fast Pedestrian Detection Using Color Information. In: Mehrotra, S., Zeng, D.D., Chen, H., Thuraisingham, B., Wang, FY. (eds) Intelligence and Security Informatics. ISI 2006. Lecture Notes in Computer Science, vol 3975. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760146_68
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DOI: https://doi.org/10.1007/11760146_68
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34478-0
Online ISBN: 978-3-540-34479-7
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