Fingertips detection and tracking based on active shape models and an ellipse
Sooyeon Kim, Younjung Park, Kyungmin Lim, Hyobin Lee, Sangki Kim, Sangyoun Lee · 2009
Detecting and tracking fingertips are significant techniques for recognizing hand gestures. Many patterns and skin color information are used to extract and trace features. However, to find correct shapes is difficult and there is limitation to express the diversity of models. In this paper, we describe a method of detecting and tracking fingertips based on Active Shape Models (ASMs) and an ellipse equation. ASM is an effective tool to obtain features of a specific object in images by using a trained model. The ellipse equation helps a template follow the object without skin color information. We show how well fingertips are extracted and traced through some experiments.