  Sign(ed) languages use gestures, such as hand or head movements, for
communication. Sign language recognition is an assistive technology for
individuals with hearing disability and its goal is to improve such
individuals' life quality by facilitating their social involvement. Since sign
languages are vastly varied in alphabets, as known as signs, a sign recognition
software should be capable of handling eight different types of sign
combinations, e.g. numbers, letters, words and sentences. Due to the intrinsic
complexity and diversity of symbolic gestures, recognition algorithms need a
comprehensive visual dataset to learn by. In this paper, we describe the design
and implementation of a Microsoft Kinect-based open source software, called
SignCol, for capturing and saving the gestures used in sign languages. Our work
supports a multi-language database and reports the recorded items statistics.
SignCol can capture and store colored(RGB) frames, depth frames, infrared
frames, body index frames, coordinate mapped color-body frames, skeleton
information of each frame and camera parameters simultaneously.
