Real-time multi-trajectory matching for dynamic hand gesture recognition

摘要

Focus on the field of dynamic gesture recognition, there is a problem of the action, is difficult to recognise when multiple fingertips move in a small range (rotation, grabbing), the authors proposed a method to get the recognition results with high robustness in real-time. Firstly, they proposed the concavity kernel accumulation algorithm (CKA) to cluster corners in an image. Secondly, they deem CKA as a region proposal generator and combined it with convolutional neural network to detect fingertips. Thirdly, they proposed the global nearest neighbour point matching algorithm to match fingertips from two frames. Finally, the long short-term memory is used in multi-trajectory recognition to get the results of gesture recognition. Experiments show that their method could recognise multi-trajectory gestures accurately, furthermore, it can run in real time (20 FPS) without graphics processing unit (GPU).