Multi-scale vehicle logo recognition by directional dense SIFT flow parsing
Qin Gu, Jianyu Yang, Guolong Cui, Lingjiang Kong, Huakun Zheng, Reinhard Klette · 2016
This paper considers robust vehicle logo recognition (without aiming at accurate location) for intelligent transportation systems. We propose a recognition-before-location framework for multi-scale vehicle logos which exploits a directional SIFT flow parsing method. We extract dense SIFT descriptors of different standard vehicle logos. An improved matching method is proposed to obtain a directional SIFT flow from standard logo models for vehicle images. Our vehicle logo recognition algorithm is based on dense SIFT matching energy and SIFT flow consistency. We verify the accuracy of vehicle logo recognition and the robustness for multi-scale logo images on various real data.