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Apr 01

Robovision’s very own Jonathan Berte and Floris De Smet have co-authored a paper on People Detection, making our SmartCity solutions faster and more scalable. Read it here.

  • 1 April 2019
  • Robovision
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  • Business

A traditional re-identification pipeline consists of a detection and re-identification step, i.e. a person detector is run on an input image to get a cutout which is then sent to a separate re-identification system. In this work we combine detection and re-identification into one single pass neural network. We propose an architecture that can do re-identification simultaneously with detection and classification. The effect of our modification has only a negligible impact on detection accuracy, and adds the calculation of re-identification vectors at virtually no cost.The resulting re-identification vector is strong enough to be used in speed sensitive applications which can benefit from an additional re-identification vector in addition to detection. We demonstrate this by using it as detection and re-identification input for a real-time person tracker. Moreover, unlike traditional detection + re-id pipelines our single-pass network’s computational cost is not dependent on the number of people in the image.

Read the full paper here.

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