Abstract 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.
Template-Based Hand Pose Recognition Using Multiple Cues
Computer Vision – ACCV 2006 ; 7 ; 551-560
Lecture Notes in Computer Science ; 3852 , 7
2006-01-01
10 pages
Article/Chapter (Book)
Electronic Resource
English
Motion Feature , Face Detection , Gesture Recognition , Oriented Edge , Hand Gesture Recognition Computer Science , Image Processing and Computer Vision , Computer Imaging, Vision, Pattern Recognition and Graphics , Pattern Recognition , Artificial Intelligence (incl. Robotics) , Algorithm Analysis and Problem Complexity
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