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: 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.

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: 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 interests with the at least a candidate region, thereby obtains the location and a complete outline of the moving object.

Abstract: A device, system, and method are directed towards providing content over a network. A test definition is defined to include at least one group of visitors and/or a range associated with the group. The test definition is then received. A plurality of requests for a first content is received from the same browser. Each of the plurality of requests includes a previously generated value (PGV)/cookie. For each of the plurality of requests, a fast-hash is performed on the same PGV/cookie to generate an identifier (e.g., number). It is then determined whether to provide a second content instead of the first content based on whether the identifier is in the range associated with the at least one group of visitors. The determination may also be based on a URL filter, a browser type, operating system type, a time-range, or an argument-value pair. The first or second content is then provided.