1. A method for recognizing a gesture performed by a user, the method comprising: acquiring a sequence of input images of a specific user; and recognizing a gesture of the specific user from the sequence of input images based on a gesture model and geometrical features extracted from a hand trajectory of the user, the recognizing further comprising: detecting abrupt changes of motion parameters of at least one object in each frame of the sequence of input images as candidate starting points of the gesture; tracking the candidate starting points though the sequence of images; matching the candidate starting points of the sequence of input images to at least one first gesture model; detecting state transition points of the at least one first matched gesture model; extracting geometrical features of a hand trajectory from the sequence of input images based on relative locations of the detected state transition points of the at least one first matched gesture model and a starting point of the gesture; computing a gesture model matching score for each frame of the sequence of input images for the candidate starting points for each gesture class using the at least one first gesture model and extracted geometrical features; pruning the at least one first matched gesture model based on the gesture model matching score of at least one frame of the sequence of input images; and classifying the gesture as the gesture class with the highest match score.
1. A method for recognizing a gesture performed by a user, the method comprising: acquiring a sequence of input images of a specific user; and recognizing a gesture of the specific user from the sequence of input images based on a gesture model and geometrical features extracted from a hand trajectory of the user, the recognizing further comprising: detecting abrupt changes of motion parameters of at least one object in each frame of the sequence of input images as candidate starting points of the gesture; tracking the candidate starting points though the sequence of images; matching the candidate starting points of the sequence of input images to at least one first gesture model; detecting state transition points of the at least one first matched gesture model; extracting geometrical features of a hand trajectory from the sequence of input images based on relative locations of the detected state transition points of the at least one first matched gesture model and a starting point of the gesture; computing a gesture model matching score for each frame of the sequence of input images for the candidate starting points for each gesture class using the at least one first gesture model and extracted geometrical features; pruning the at least one first matched gesture model based on the gesture model matching score of at least one frame of the sequence of input images; and classifying the gesture as the gesture class with the highest match score. 3. The method as in claim 1 , wherein the recognizing step further comprises: determining an endpoint of the gesture based on the at least one first matched gesture model and the extracted geometrical features; and backtracking through the images from the determined endpoint of the gesture to determine an actual starting point of the gesture.