Stereo Vision Tracking of Multiple Objects in Complex Indoor Environments

Sensors

Marta Marrón-Romera¹  Juan C. Garc໚¹  Miguel A. Sotelo¹  Daniel Pizarro¹  Manuel Mazo¹  José M. Ca༚s²  Cristina Losada¹ 

[1] Electronics Department, University of Alcalá, Campus Universitario s/n, 28805, Alcalá de Henares, Madrid, Spain; E-Mails:;Departamento de Sistemas Telemáticos y Computación, Universidad Rey Juan Carlos, C/Tulipán s/n, 28933, Móstoles, Madrid, Spain; E-Mail:

关键词: 3D tracking;    Bayesian estimation;    stereo vision sensor;    mobile robots;   

DOI  :  10.3390/s101008865

来源: mdpi

【 摘 要 】

This paper presents a novel system capable of solving the problem of tracking multiple targets in a crowded, complex and dynamic indoor environment, like those typical of mobile robot applications. The proposed solution is based on a stereo vision set in the acquisition step and a probabilistic algorithm in the obstacles position estimation process. The system obtains 3D position and speed information related to each object in the robot’s environment; then it achieves a classification between building elements (ceiling, walls, columns and so on) and the rest of items in robot surroundings. All objects in robot surroundings, both dynamic and static, are considered to be obstacles but the structure of the environment itself. A combination of a Bayesian algorithm and a deterministic clustering process is used in order to obtain a multimodal representation of speed and position of detected obstacles. Performance of the final system has been tested against state of the art proposals; test results validate the authors’ proposal. The designed algorithms and procedures provide a solution to those applications where similar multimodal data structures are found.

【 授权许可】

CC BY   
© 2010 by the authors; licensee MDPI, Basel, Switzerland.