CAJ | 학술논문

鉴于无接触体感交互技术在人机交互领域的成功应用，提出了一种基于Kinect深度相机的实时隔空虚拟书写方法。结合颜色和深度数据检测和分割出手掌区域；进一步，通过修改的圆扫描转换算法获得手指的个数，以识别不同的手势指令；根据指尖检测从指尖的运动轨迹分割出独立的字符或汉字运动轨迹，并采用随机森林算法识别该字符或汉字。这种基于深度信息的手势检测和虚拟书写方法可以克服光照和肤色重叠的影响，可靠实时地检测和识别手势和隔空书写的文字，其识别率达到93.25%，识别速度达到25 frame/s。
감우무접촉체감교호기술재인궤교호영역적성공응용，제출료일충기우Kinect심도상궤적실시격공허의서사방법。결합안색화심도수거검측화분할출수장구역；진일보，통과수개적원소묘전환산법획득수지적개수，이식별불동적수세지령；근거지첨검측종지첨적운동궤적분할출독립적자부혹한자운동궤적，병채용수궤삼림산법식별해자부혹한자。저충기우심도신식적수세검측화허의서사방법가이극복광조화부색중첩적영향，가고실시지검측화식별수세화격공서사적문자，기식별솔체도93.25%，식별속도체도25 frame/s。
Inspired by the successful application of the contactless somatosensory interaction technology in the field of human-computer interaction, this paper presents a real-time Kinect depth camera based contactless virtual hand writing technique. In the technique, hand regions are detected and segmented utilizing both color and depth information. Hand fingers are rapidly recognized using a modified scan conversion method of a circle in order to recognize different hand gestures. It uses tracking by detection of a fingertip to obtain the fingertip trajectory and segment out individual trajectories for English and Chinese characters. Further a random forests algorithm is used to identify the correct characters from these individual trajectories. This depth information based hand gesture recognition and virtual hand writing technique can overcome the effects of light and color overlap and make the real-time detection and identification of gestures and hand writing more robust and reliable. The recognition accuracy can arrive at 93.25%and the speed of the recognition is about 25 frame/s.