Robust Pedestrian Tracking in Crowd Scenarios Using an Adaptive GMM-based Framework
Shuyang Zhang,Di Wang,Fulong Ma,Chao Qin,Zhengyong Chen,Ming Liu,Shuyang Zhang,Di Wang,Fulong Ma,Chao Qin,Zhengyong Chen,Ming Liu
In this paper, we address the issue of pedestrian tracking in crowd scenarios. People in close social relationships tend to act as a group which is a great challenge to individually discriminate and track pedestrians on a LiDAR system. In this paper, we integrally model groups of people and track them in a recursive framework based on Gaussian Mixture Model (GMM). The model is optimized by an exte...
