Multiple curvature based approach to human upper body parts detection with connected ellipse model fine-tuning

In this paper, we discuss an effective method for detecting human upper body parts from a 2D image silhouette using curvature analysis and ellipse fitting. First we smooth the silhouette so that we can determine just the global features: the head, hands and armpits. Next we reduce the smoothing to detect the local features of the neck and elbows. We model the human upper body by multiple connected ellipses. Thus we segment the body by the extracted features. Ellipses are fitted to each segment. Lastly, we apply a nonlinear least square method to minimize the differences between the connected ellipse model and the edge of the silhouette.