Chinese Sign Language Recognition Research Using SIFT-BoW and Depth Image Information
Yang Qua · 2014
Introducing the depth image information into sign language recognition research,a Chinese sign language recognition method based on DI_CamShift(Depth Image CamShift)and SIFT-BoW(Scale Invariant Feature TransformBag of Words)was presented.It uses Kinect as the video capture device to obtain both of the color video and depth image information of sign language.First,it calculates spindle direction angle and mass center position of the depth image correctly tracks gesture by adjusting the search window.Second,an Ostu algorithm based on depth integral image is used to gesture segmentation,and the SIFT features are extracted.Finally,it builds SIFT-BoW as the feature of sign language and uses SVM for recognition.The experimental results show that the best recognition rate of single manual alphabet can reach 99.87%,while the average recognition rate is 96.21%.