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. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Stenger, B. (2006). Template-based hand pose recognition using multiple cues. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3852 LNCS, pp. 551–560). https://doi.org/10.1007/11612704_55
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