基于多重分形分析的行人检测

Baochang Zhang, Hainan Wang, Hong Zheng, Ya-wei Hou, Chenglong He, Baoguo Yu
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引用次数: 1

摘要

提出了一种新的基于多重分形分析的特征表示方法。计算多重分形维数(Multiple Fractal Dimensions, MFD)来描述从图像中提取的有限个数的点集上测量的分形维数的分布。所提出的MFD特征在理论上被证明是不受关节的影响的,由于存在表情、姿势和照明变化,这是人脸和行人的理想特征。新的目标表示在行人检测问题上得到了广泛的评价。INRIA行人数据库的实验表明,该方法在识别率方面比基线方法取得了更好的性能。
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Pedestrian detection based on multifractal analysis
This paper proposes a new multifractal analysis based feature representation for object representation. Multiple Fractal Dimensions (MFD) are calculated to describe the distribution of fractal dimensions measured on a finite number of point sets extracted from the image. The proposed MFD feature is theoretically proven to be invariant to articulations, which is a desirable characteristic for faces and pedestrian due to the existence of expressions, posture and illumination variations. The new object representation is extensively evaluated on pedestrian detection problem. The experiments INRIA pedestrian databases show that our method achieves a much better performance than baseline methods in terms of recognition rates.
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