摘要:
An object detection method and an object detection system, suitable for detecting moving object information of a video stream having a plurality of images, are provided. The method performs a moving object foreground detection on each of the images, so as to obtain a first foreground detection image comprising a plurality of moving objects. The method also performs a texture object foreground detection on each of the images, so as to obtain a second foreground detection image comprising a plurality of texture objects. The moving objects in the first foreground detection image and the texture objects in the second foreground detection image are selected and filtered, and then the remaining moving objects or texture objects after the filtering are output as real moving object information.
摘要:
An object detection method and an object detection system, suitable for detecting moving object information of a video stream having a plurality of images, are provided. The method performs a moving object foreground detection on each of the images, so as to obtain a first foreground detection image comprising a plurality of moving objects. The method also performs a texture object foreground detection on each of the images, so as to obtain a second foreground detection image comprising a plurality of texture objects. The moving objects in the first foreground detection image and the texture objects in the second foreground detection image are selected and filtered, and then the remaining moving objects or texture objects after the filtering are output as real moving object information.
摘要:
A multi-state target tracking method and a multi-state target tracking system are provided. The method detects a crowd density of a plurality of images in a video stream and compares the detected crowd density with a threshold when receiving the video stream, so as to determine a tracking mode used for detecting the targets in the images. When the detected crowd density is less than the threshold, a background model is used to track the targets in the images. When the detected crowd density is greater than or equal to the threshold, a none-background model is used to track the targets in the images.