Improved SURF algorithm based on proportional distance and angle for static sign language recognition
M.Z. Yang Y. Luo Y. Wang · 2015
In recent years, with the continuous development of machine vision technology, sign language recognition based on vision is becoming a research hotspot issue. Anant Agarwal, Manish K Thakur [1], and Quan Yang [2] all used Kinect sensor to access the depth image for sign language recognition. Recent years, Chongqing information accessibility and service robot engineering technology search center has applied SURF characteristics to identify the static alphabet and obtained good recognition results [3]. Zhiqiang Wei used the method which Euclidean distance is performed to get exact matching to avoid wrong matching [4].