Template-Based Hand Pose Recognition Using Multiple Cues

This paper presents a practical method for hypothesizing hand locations and subsequently recognizing a discrete number of poses in image sequences. In a typical setting the user is gesturing in front of a single camera and interactively performing gesture input with one hand. The approach is to identify likely hand locations in the image based on discriminative features of colour and motion. A set of exemplar templates is stored in memory and a nearest neighbour classifier is then used for hypothesis verification and pose estimation. The performance of the method is demonstrated on a number of example sequences, including recognition of static hand gestures and a navigation by pointing application.

• Type: Conference
• Year: 2006
• Where: ACCV
• Authors: Björn Stenger
• Keywords: ACCV 2006, Computer Vision, Hand Locations, Likely Hand Locations, Static Hand Gestures