Object recognition in visual sensor networks based on compression and transmission of binary local features
نویسندگان
چکیده
This demo features a multi-hop Visual Sensor Network, capable of recognizing objects using two different visual paradigms. In the traditional compress-then-analyze (CTA) paradigm, JPEG compressed images are transmitted through the network from a camera node to a central controller, where the analysis takes place. In the alternate analyze-then-compress (ATC) paradigm, the camera node extracts and compresses local binary visual features from the acquired images and transmits them to the central controller, where they are used to perform object recognition. We show that, in a bandwidth constrained scenario, the latter paradigm allows to reach higher application framerates, still ensuring excellent recognition results.
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