TITLE:
Multi-Scale Human Pose Tracking in 2D Monocular Images
AUTHORS:
Jinglan Tian, Ling Li, Wanquan Liu
KEYWORDS:
Human Motion Tracking; Multi-Scale; 2D; Monocular Video
JOURNAL NAME:
Journal of Computer and Communications,
Vol.2 No.2,
January
10,
2014
ABSTRACT: In this paper we address the problem of tracking
human poses in multiple perspective scales in 2D monocular images/videos. In
most state-of-the-art 2D tracking approaches, the issue of scale variation is
rarely discussed. However in reality, videos often contain human motion with dynamically
changed scales. In this paper we propose a tracking framework that can deal
with this problem. A scale checking and adjusting algorithm is proposed to
automatically adjust the perspective scales during the tracking process. Two
metrics are proposed for detecting and adjusting the scale change. One metric
is from the height value of the tracked target, which is suitable for some
sequences where the tracked target is upright and with no limbs stretching. The
other metric employed in this algorithm is more generic, which is invariant to
motion types. It is the ratio between the pixel counts of the target silhouette
and the detected bounding boxes of the target body. The proposed algorithm is
tested on the publicly available datasets (HumanEva).
The experimental results show that our method demonstrated higher accuracy and
efficiency compared to state-of-the-art approaches.