JU_V2_DATASET

Reliable hand gesture recognition is an important problem for automatic sign language recognition for the people with hearing and speech disabilities. For this purpose, we have created a new benchmark database of multi-oriented, isolated, static ASL digit and alphabet images using depth sensor Microsoft Kinect V2. Further, we design a statistical-geometrical feature combination for recognition of the hand gestures out of our dataset. We have collected data for JU_V2_DIGIT dataset from 0 to 9 and for JU V2 ALPHA dataset from a to z.