A single-view based framework for robust estimation of heights and positions of moving people
Seok‐Han Lee, Tae-Eun Kim, Jong-Soo Choi · 2010
In recent years, there has been increased interest in characterizing 3D information from video sequences for human tracking/identification. In this paper, we propose a single view-based framework for robust estimation of height and position. In the proposed work, 2D features of a target object are back-projected into the 3D scene where its coordinate system is given by a rectangular marker. Then the position and height are measured in the scene space. In addition, geometric error caused by inaccurate projective mapping is corrected by using geometric constraints provided by the marker. The accuracy and robustness are verified on the experimental results of several video sequences from outdoor environments.