Due to the universal non-verbal natural communication approach that allows for effective communication between humans, gesture recognition technology has been steadily developing over the previous few decades. Many different strategies have been presented in research articles based on gesture recognition to try to create an effective system to send non-verbal natural communication information to computers, using both physical sensors and computer vision. Hyper accurate real-time systems, on the other hand, have only recently began to occupy the study field, with each adopting a range of methodologies due to past limits such as usability, cost, speed, and accuracy. A real-time computer vision-based human-computer interaction tool for gesture recognition applications that acts as a natural user interface is proposed. Virtual glove markers on users hands will be created and used as input to a deep learning model for the real-time recognition of gestures. The results obtained show that the proposed system would be effective in real-time applications including social interaction through telepresence and rehabilitation.
翻译:由于普遍的非口头自然通信方法使得人类之间能够进行有效的交流,在过去几十年中,姿态识别技术一直在稳步发展,在基于姿态确认的研究文章中提出了许多不同的战略,以试图建立一个有效的系统,利用物理传感器和计算机视觉向计算机发送非口头自然通信信息。另一方面,超精确的实时系统直到最近才开始占据研究领域,每个系统都采用一系列方法,因为过去的限制,如可用性、成本、速度和准确性等。一个基于计算机的实时基于视觉的人体计算机互动工具,用于作为自然用户界面的手势识别应用。将创建用户手中的虚拟手套标记,并用作实时识别姿态的深层学习模式的投入。获得的结果显示,拟议的系统将在实时应用中有效,包括通过远程和康复进行社会互动。