We show the demonstration video of our research in Youtube:
Grasp of congestion situation and flow of persons and cars in time of disaster is important for reducing human damage. There are many researches and developments for obtaining the information by analyzing images and videos captured by a camera on an airplane or a drone. However conventional methods (optical flow, particle filter, Kalman filter, statistical processing of time-space voxel code, etc.) are not enough to grasp situation by detecting motion of each person and each car so far. The segmentation problem of moving persons and moving cars in images or videos is not well solved.
A new algorithm should be developed so that it can detect motion of each person and each car in a wide area from a video in the way that it works easily, quickly, automatically, in real time, for a long time video, and specially realizing segmentation-free characteristics of persons and cars in images or videos. This kind of task is not realized by using a laser or an infrared sensors because the scene is capturing by a video camera in the sky.
Our algorithm called Time-Space Continuous Dynamic Programming (TSCDP)can detect motion in the way mentioned in the above including the solution of segmentation-free problem.
We show two experimental results for detecting motion of many persons and cars (see pictures). The first one is detection of motion of each football player during the game on the field from a video captured by a camera. The second one is motion detection of each walking person and each moving car on the road from a video. A person walking along a sidewalk is detected. Different colors in the
scene images indicate different motions of moving objects.
The experimental results show surely the potential of TSCDP for grasping congestion situation and flow of persons and cars in time of disaster. The patent of this method has been registered.
Recently, drones become popular for using them in many application domains. We need now to develop new algorithms which are applicable to data obtained by drones and obtain actual useful information. These works are mainly belonging to not hardware but software.
 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.