DocumentCode :
3116162
Title :
A Novel Algorithm for Moving Objects Recognition Based on Sparse Bayesian Classification
Author :
Changhua, Lu ; Ningning, Chang ; Rui, Fang ; Chun, Liu
Author_Institution :
Sch. of Comput. & Inf., Hefei Univ. of Technol., Hefei
fYear :
2006
fDate :
6-8 Sept. 2006
Firstpage :
135
Lastpage :
139
Abstract :
This paper deals with the problem of moving objects recognition using Bayesian method. A novel algorithm based on sparse Bayesian classification for the recognition of moving objects is proposed. This approach takes full advantage of sparse Bayesian in solving classification problems. It uses fewer kernel functions in order to reduce the complexity of the computation and resolves the over-fitting problem in recognition system. The experimental results show that this approach distinctly outperforms other classification approaches on this issue. The veracity and velocity are also satisfactory.
Keywords :
Bayes methods; computational complexity; image classification; image motion analysis; object recognition; computation complexity reduction; kernel function; moving object recognition; sparse Bayesian classification; Automatic control; Bayesian methods; Control systems; Feature extraction; Image recognition; Kernel; Lighting; Object recognition; Support vector machine classification; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning for Signal Processing, 2006. Proceedings of the 2006 16th IEEE Signal Processing Society Workshop on
Conference_Location :
Arlington, VA
ISSN :
1551-2541
Print_ISBN :
1-4244-0656-0
Electronic_ISBN :
1551-2541
Type :
conf
DOI :
10.1109/MLSP.2006.275536
Filename :
4053635
Link To Document :
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