Yunyun Cao

Local Binary Pattern features for pedestrian detection at night/dark environment

Being fast to compute and simple to implement, Local Binary Pattern (LBP) has also shown superior performance in texture classification and face detection. However, it is not well optimized for pedestrian detection. At night/dark environment, pedestrian detection typically needs to overcome problems of low contrast, image blur, and image noise. A novel feature extraction method, consisting of Weighted LBP, Multi-resolution LBP, and Multi-scale LBP, is proposed to solve them. Experimental results show that the proposed method improves upon the basic LBP significantly and outperforms benchmarks such as HOG and CoHOG.

Stagged multi-scale LBP for pedestrian detection

Pedestrian detection remains a popular and challenging problem due to large variation in appearance. A robust feature extraction method is highly desired for accurate pedestrian detection. In this paper, firstly, we propose a staggered multiscale LBP histogram. In order to exploit grayscale difference information in more directions, three scales with radius of 1, 3, and 5 pixels are utilized, and different scales are staggered. The Staggered Multi-scale LBP histogram is composed of three 256-bin histograms, each of which corresponds to one of the three scales. Secondly, dimensionality of the LBP histogram is reduced using a boosting learning method. Experimental results show that the proposed feature outperforms benchmarks such as Uniform-LBP, HOG and CoHOG on INRIA, Daimler Chrysler and our Panasonic night time datasets.

79GHz-band radar cross section measurement for pedestrian detection

This paper presents radar cross section (RCS) measurement for pedestrian detection in 79GHz-band radar system. For a human standing at 6.2 meters, the RCS distributions median value is -11.1 dBsm and the 90 % of RCS fluctuation is between -20.7 dBsm and -4.8 dBsm. Other measurement results (human body poses beside front) are shown. And we calculated the coefficient values of the Weibull distribution fitting to the human body RCS distribution.