Open AccessCooperative object tracking using dual‐pan–tilt–zoom cameras based on planar ground assumption
Author(s) -
Cui Zhigao,
Li Aihua,
Feng Guoyan,
Jiang Ke
Publication year - 2015
Publication title -
iet computer vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.38
H-Index - 37
eISSN - 1751-9640
pISSN - 1751-9632
DOI - 10.1049/iet-cvi.2013.0246
Subject(s) - computer vision , computer science , artificial intelligence , homography , zoom , video tracking , object (grammar) , tracking (education) , ground plane , camera resectioning , tilt (camera) , constraint (computer aided design) , tracking system , mathematics , kalman filter , psychology , telecommunications , pedagogy , statistics , geometry , projective test , projective space , petroleum engineering , antenna (radio) , engineering , lens (geology)
Pan–tilt–zoom (PTZ) cameras play an important role in visual surveillance system. Dual‐PTZ camera system is the simplest and most typical one. The superiority of this system lies in that it can obtain both large‐view information and high‐resolution local‐view information of the tracked object at the same time. One method to achieve such task is to use master–slave configuration. One camera (master) tracks moving objects at low resolution and provides the positional information to another camera (slave). Then the slave camera can point towards the object at high resolution and track it dynamically. In this paper, we propose a novel framework exploiting planar ground assumption to achieve cooperative tracking. The approach differs from conventional methods in that we exploit planar geometric constraint to solve the camera collaboration problem. Compared with the existing approach, the proposed framework can be used in the case of wide baseline, and allows the depth change of the tracked object. The proposed method can also adapt to the dynamic change of the surveillance scene. Besides, we also describe a self‐calibration method of homography matrix which is induced by the ground plane between two cameras. We demonstrate the effectiveness of the proposed method by testing it with a tracking system for surveillance applications.