Simultaneous localization and recognition of dynamic hand gestures

A method for the simultaneous localization and recogni-tion of dynamic hand gestures is proposed. At the core of this method is a dynamic space-time warping (DSTW) al-gorithm, that aligns a pair of query and model gestures in both space and time. For every frame of the query sequence, feature detectors generate multiple hand region candidates. Dynamic programming is then used to compute both a global matching cost, which is used to recognize the query gesture, and a warping path, which aligns the query and model sequences in time, and also finds the best hand candidate region in every query frame. The proposed frame-work includes translation invariant recognition of gestures, a desirable property for many HCI systems. The perfor-mance of the approach is evaluated on a dataset of hand signed digits gestured by people wearing short sleeve shirts, in front of a background containing other non-hand skin-colored objects. The algorithm simultaneously localizes the gesturing hand and recognizes the hand-signed digit. Al-though DSTW is illustrated in a gesture recognition setting, the proposed algorithm is a general method for matching time series, that allows for multiple candidate feature vec-tors to be extracted at each time step. 1