以積體電路設計自適應性物件偵測法應用於視覺監(jiān)控系統(tǒng)簡介——第三屆OpenHW開放源碼硬件與嵌入式大賽三等獎
所屬分類：其他
上傳者：chenyy
文檔大?。?span>953 K
標簽： FPGA
所需積分：0分積分不夠怎么辦？
文檔介紹：This work presents a new model based on least-mean-square (LMS) scheme to train the mask operation on low resolution images. This efficient and real-time method with adaptive least-mean-square scheme (ALMSS) uses the training mask for moving objects detection and tracking on resource-limited systems. However, the scheme of moving objects detection and tracking in a real surrounding environment is a difficult task due to noise issues such as fake motion or noise. The ALMSS approach can effectively reduce the noise with low computing cost in both fake motion and noise environments. In the experiments on real scenes indicate that the proposed ALMSS method is effective for moving objects detection and tracking in real-time. Our approach can be implemented in hardware for the high resolution applications, such as Full-HD images. A prototype VLSI circuit was designed and simulated by TSMC 0.18mm 1P6M process.
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