Recognizing Temporal Trajectories Using the Condensation Algorithm
نویسندگان
چکیده
The recognition of human gestures in image sequences is an important and challengingproblem that enables a host of human-computer interaction applications. This paper describes an incremental recognition strategy that is an extension of the “Condensation” algorithm proposed by Isard and Blake (ECCV’96). Gestures are modeled as temporal trajectories of some estimated parameter over time (in this case velocity). The condensation algorithm is used to incrementally match the gesture models to the input data. The method is demonstrated with an example of an augmented office whiteboard in which a user makes simple hand gestures to grab regions of the board, print them, save them, etc.
منابع مشابه
Gesture recognition using position and appearance features
In this paper a scheme for recognizing hand gestures is presented using the output of a Condensation tracker. The tracker is used to obtain a set of features. These features consisting of temporal evolution of the spatial moments form high dimensional feature vectors. The principal components of the feature trajectories are used to recognize the gestures.
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