Cross Cameras Bicycle Re-identification for Mixed Traffic Intersections

In order to obtain the precise dynamic track data from cross camera bicycle under the mixed traffic flow intersections, the experimental research was carried out in regard of the re-identification problem in the process of the cross camera bicycle track. The cross camera bicycle re-identification algorithm under the mixed traffic intersections based on the sample sequence grouping similarity measurement was proposed, with the considerations of complex environment of the mixed traffic intersections, illumination variation and the differences of camera view. In terms of the statistic method, the bicycle sample was divided into three parts and then the ratio of split was cumulated. Through extracting the features from the parts of bicycle gallery, corresponding prototype features were obtained by clustering analysis. With the sample sequence replacing the single sample as a probe, the quantitative analysis of samples was carried out based on comparison analysis. The feature of robustness design was analyzed and a more abstract prototype similarity feature was obtained after the similarity measurement of each sample part and its prototype. Similarity of samples was calculated by within-group linkage and no linkage between groups to improve the time complexity of algorithm by grouping sample sequence with the systematic sampling. In order to analyze the performance of the algorithm, BIKE1, the bicycle re-identification dataset was collected. Meanwhile group performance assessment, prototype parameter settings of components and similar algorithm performance comparison were experimentally compared. The results show that higher identification accuracy is gotten by regarding the sample sequence as a probe, especially when sample sequence is divided into two groups. The bicycle sample, divided into three parts, efficiently strengthens the robustness of influence of algorithm on the illumination variation. Compared with other similar algorithms, identification rate of the above algorithm is much higher. © 2017, Editorial Department of China Journal of Highway and Transport. All right reserved.