Tuyển tập các báo cáo nghiên cứu về hóa học được đăng trên tạp chí hóa hoc quốc tế đề tài : Multi-camera multi-object voxel-based Monte Carlo 3D tracking strategies | Canton-Ferrer et al. EURASIP Journal on Advances in Signal Processing 2011 2011 114 http content 2011 1 114 o EURASIP Journal on Advances in Signal Processing a SpringerOpen Journal RESEARCH Open Access Multi-camera multi-object voxel-based Monte Carlo 3D tracking strategies Cristian Canton-Ferrer Josep R Casas Montse Pardàs and Enric Monte Abstract This article presents a new approach to the problem of simultaneous tracking of several people in low-resolution sequences from multiple calibrated cameras. Redundancy among cameras is exploited to generate a discrete 3D colored representation of the scene being the starting point of the processing chain. We review how the initiation and termination of tracks influences the overall tracker performance and present a Bayesian approach to efficiently create and destroy tracks. Two Monte Carlo-based schemes adapted to the incoming 3D discrete data are introduced. First a particle filtering technique is proposed relying on a volume likelihood function taking into account both occupancy and color information. Sparse sampling is presented as an alternative based on a sampling of the surface voxels in order to estimate the centroid of the tracked people. In this case the likelihood function is based on local neighborhoods computations thus dramatically decreasing the computational load of the algorithm. A discrete 3D re-sampling procedure is introduced to drive these samples along time. Multiple targets are tracked by means of multiple filters and interaction among them is modeled through a 3D blocking scheme. Tests over CLEAR-annotated database yield quantitative results showing the effectiveness of the proposed algorithms in indoor scenarios and a fair comparison with other state-of-the-art algorithms is presented. We also consider the real-time performance of the proposed algorithm. 1 Introduction Tracking multiple objects and keeping record of their identities along time in a cluttered dynamic scene
