SignCol: Open-Source Software for Collecting Sign Language Gestures
This work provides a tool for researchers to collect data for sign language recognition, an assistive technology aimed at improving social involvement for individuals with hearing disabilities, but it is incremental as it builds on existing hardware and focuses on data collection rather than novel recognition methods.
The authors tackled the lack of comprehensive visual datasets for sign language recognition by developing SignCol, an open-source software using Microsoft Kinect to capture and store multiple data types like RGB, depth, and skeleton frames, supporting a multi-language database and reporting recorded item statistics.
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.