A robust approach for person localization in multi-camera environment

Person localization is fundamental in human centered computing, since person should be localized before being actively serviced. This paper proposed a robust approach to localize person based on the geometric constraints in multi-camera environment. The proposed algorithm has several advantages: 1) no assumption on the positions and orientations of cameras except the cameras should have certain common field of view; 2) no assumption on the visibility of particular body part (e.g., feet), except a portion of person should be observed in at least two views; 3) reliability in terms of tolerating occlusion, body posture change and inaccurate motion detection. It can also provide error control and be further extended to measure person height. The efficacy of the approach is demonstrated on challenging real-world scenarios.