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发展强大的事件驱动的高效MCU视频监控系统
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2017-05-12
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发展强大的事件驱动的高效MCU视频监控系统
当涉及到视频监控，设计师和他们的客户一直被迫接受效率极低的系统，依靠“哑巴”批量图像捕获和归档，对不感兴趣的记录内容的绝大多数，和本身的兴趣，太难找到档案中的内容，假设它已经存档。现在，然而，强大的功率效率和成本效益的处理器，图像传感器和存储设备，结合日益复杂的软件系统开发商提供的机会，把宝贵的计算机视觉处理能力的应用范围从消费者监控系统可穿戴的“lifeblogging”相机。
智能的，事件驱动的，视频监控只记录图像时，例如，一个人或其他感兴趣的对象进入帧，并且只要对象保持在帧中。这样的自主智能可能历史上只有在昂贵，笨重，用政府权力饥渴的设备、军事等高端客户，现在可以在消费者的价格交付，电池寿命长，在一个小的形式因素和足够轻的美观，坐在架子上。
What can you do with the potential delivered by today‘s vision processing hardware and software？ Here are some ideas， based on a consumer surveillance system case study：
An elementary design might begin recording whenever it sensed motion in the frame， and for a fixed amount of time. A slightly more elaborate approach would variable-length record until it was discerned that object motion had ceased and/or the object had disappeared from the frame.
Such an approach， however， might generate lots of “false positives” caused by blowing leaves， passing-by vehicles， and the like. If warm-blooded animals are the only objects of interest， therefore， you might want to supplement the visible-light camera with an IR detector or other thermal sensor. More generally， available algorithms will let you fine-tune your object “trigger” for size， color， distance， movement rate， and other threshold parameters.
What if discerned humans are all that you care about？ A face detection function can assist in this regard. You might even be interested in triggering the camera whenever a person enters the frame.。.unless that person is yourself， your spouse， one of your kids， the mailman， etc. For this， you’ll need more robust facial recognition facilities.
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