| 摘要(英) |
Recently, video surveillance and monitoring (VSAM) has gradually become a popular research topic due to its importance. In such systems, the main tasks to be performed can be summarized as follows; image sequences are processed, moving targets are detected and tracked, video data are stored and queried, and alarms are made when illegal events occur. Many topics focus on the study of image processing, pattern recognition, and artificial intelligence.
In this thesis, an immersed environment is developed by combining virtual reality and video monitoring methodologies. The image sequences are grabbed to construct the panoramic images from a programmable controlled PTZ camera. These images are stitched by using the moisack techniques. In addition, moving targets are detected, tracked and segmented from the video sequences. Moreover, the PTZ camera is triggered by the predicted data in order to continuously capture the images with moving targets when objects are out of the field of view (FOV). Two experimental environments, an indoor scene and an outdoor scene, are constructed to demonstrate the validity and effectiveness of our proposed approach. |
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