We show the demonstration video of our research in Youtube.


We proposed a matching algorithm called Time-space Continuous Dynamic Programming (TSCDP) [1] for segmentation-free recognition of complex and multiple motions from a video stream. Segmentation-free characteristics work in both time and spatial position so that determination of both starting and ending times of each motion is not required, and any spatial position of each motion is allowed for recognition.

  Moreover, multiple and complex motions in a scene are also recognized. Moving background and occlusion are also allowed. Real-time and segmentation-free recognition is available for spotting recognition of sport motions such as performance of figure skating and sumo etc. and it is useful for realizing automatic scoring and/or decision of win or loss.
The video captured by a moving camera is allowed. 

 These functions have not been realized by conventional methods including HMM etc. so far. 

 There are many other sensors using infrared (Kinect etc.) and laser devices, and  accelerometer for capturing human motions. However the realization of these functions are out of scope even we use these devices. 

  The figures are showing several applications of motion recognition including complex and connected Chinese characters and also new functions such as detection of moving cars realized by TSCDP. The realized functions provide actual and ideal solutions which have been required to realize the real world applications of motion recognition technology. The patent of this method has been registered.

[1] Yuki Niitsuma, Syunpei Torii, Yuichi Yaguchi & Ryuichi Oka:"Time-segmentation and position-free recognition of air-drawn gestures and characters in videos", Multimedia Tools and Applications, An International Journal, ISSN 1380-7501, Volume 75, Number 19, pp.11615--11639.

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Areas of Activity
others. Motion recognition from a video, Pattern recognition
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