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Vehicle object retargeting from dynamic traffic videos for real-time visualisation

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Abstract

One form of video visualisation is to transform traffic videos from a street view to an aerial view, which facilitates a summary overview of multiple traffic video streams. This paper presents an efficient and effective solution to mitigate the undesirable distortion of the re-targeted vehicle objects in traffic video visualisation. This is achieved by a series of automated algorithmic steps, including vehicle segmentation, vehicle roof detection, and non-uniform image deformation by applying a second homography. This technique has been integrated into a video visualisation system that creates an aerial view of re-targeted video streams on top of a conventional aerial view. The results have shown that the technique offers the system a significant improvement in visual quality without undermining the requirement for real-time video visualisation.

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Authors and Affiliations

  1. University of Oxford, Oxford, UK

    Simon Walton, Kai Berger, David Ebert & Min Chen

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  1. Simon Walton
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  2. Kai Berger
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  3. David Ebert
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  4. Min Chen
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Corresponding author

Correspondence to Kai Berger.

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Walton, S., Berger, K., Ebert, D. et al. Vehicle object retargeting from dynamic traffic videos for real-time visualisation. Vis Comput 30, 493–505 (2014). https://doi.org/10.1007/s00371-013-0874-5

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