Edge-Based Rich Representation for Vehicle Classification

In this paper we propose an approach to vehicle classification under a mid-field surveillance framework. We develop a repeatable and discriminative feature based on edge points and modified SIFT descriptors, and introduce a rich representation for object classes. Experimental results show the proposed approach is promising for vehicle classification in surveillance videos despite great challenges such as limited image size and quality and large intra-class variations. Comparisons demonstrate the proposed approach outperforms other methods.

• Type: Conference
• Year: 2005
• Where: ICCV
• Authors: Xiaoxu Ma, W. Eric L. Grimson
• Keywords: Approach Outperforms, Computer Vision, ICCV 2005, Limited Image Size, Mid-field Surveillance Framework, Sift Descriptors, Vehicle Classification