Abstract: 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.

Abstract: A multi-layered glass structure includes at least three glass substrates. The edges of the three glass substrates are sealed and fastened. There is a cavity space between two adjacent glass substrates, and the multi-layered glass structure includes at least one vacuum cavity space. The multi-layered glass structure has a flat vacuum structure to enhance the heat insulation and separating effect and the noise insulation effect of the multi-layered glass structure.

Abstract: A pixel region-based image segmentation method is disclosed. When an input image is retrieved, pixels thereof are sequentially scanned row by row. Signs of unmarked pixels of the input image are determined according to region features of neighboring pixels of each pixel and pixel update information is recorded to generate a region sign update data table and a region sign feature data table. The pixels of the input frame are further scanned row by row to retrieve signs of the pixels and region signs of the pixels are determined and updated according to the region sign update data table.

Abstract: A method for tracking a moving object is provided. The method detects the moving object in a plurality of continuous images so as to obtain space information of the moving object in each of the images. In addition, appearance features of the moving object in each of the images are captured to build an appearance model. Finally, the space information and the appearance model are combined to track a moving path of the moving object in the images. Accordingly, the present invention is able to keep tracking the moving object even if the moving object leaves the monitoring frame and returns again, so as to assist the supervisor in finding abnormal acts and making following reactions.

Abstract: A method for detecting a shadow of an object in an image is provided. A moving object in a plurality of continuous images is detected. A histogram of a color variation of the moving object in each of the images is calculated. The histograms of the color variation are accumulated to obtain a cumulative histogram. A distribution of the color variation in the cumulative histogram is estimated to obtain a shadow distribution function. Whether each pixel in a received image belongs to the shadow is determined by using the shadow distribution function.