Industrial Technology Research Institute

Cheng-Chuan Chou

Chung-Hsien Huang

Ming-Yu Shih

Yi-Ta Wu

Chao-Hung Kao

Ruei-Cheng Wu

An object tracking method for a non-overlapping-sensor network works in a sensor network. The method may comprise a training phase and a detection phase. In the training phase, a plurality of sensor information measured by the sensors in the sensor network is used as training samples. At least an entrance/exit is marked out within the measurement range of each sensor. At least three characteristic functions including sensor spatial relation among the sensors in the sensor network, difference of movement time and similarity in appearance, are estimated by an automatically learning method. The at least three characteristic functions are used as the principles for object tracking and relationship linking in the detection phase.

Object Tracking method and apparatus for a non-overlapping-sensor network

An apparatus and method for moving object detection computes a corresponding frame difference for every two successive image frames of a moving object, and segments a current image frame of the two successive image frames into a plurality of homogeneous regions. At least a candidate region is further detected from the plurality of homogeneous regions. The system gradually merges the computed frame differences via a morphing-based technology and fuses the merged frame difference with the at least a candidate region, thereby obtaining the location and a complete outline of the moving object.

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Kaohsiung, Taiwan

Cheng-Chuan Chou