Transcription of An Experimental Study on Pedestrian Classification
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An Experimental Study on Pedestrian Classification
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 28, NO. 11, NOVEMBER 2006 1. An Experimental Study empirically. In addition, we Study the correlation of Classification performance with training sample size and investigate two on Pedestrian Classification techniques for the automatic generation of new training examples. By making the data set publicly available for benchmarking S. Munder and Gavrila purposes, we aim to advance further research in Pedestrian Classification analogous to, , the contribution of the Abstract Detecting people in images is key for several important application FERET database [2] toward face domains in computer vision. This paper presents an in-depth Experimental Study The remainder of this paper is organized as follows: After on Pedestrian Classification ; multiple feature-classifier combinations are examined reviewing existing techniques in Section 2, we first describe our with respect to their ROC performance and efficiency.
An Experimental Study on Pedestrian Classification S. Munder and D.M. Gavrila Abstract—Detecting people in images is key for several important application
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