Abstract
The modern automotive industry has to meet the requirement of providing a safer, more comfortable and interactive driving experience. Depth information retrieved from a stereo vision system is one significant resource enabling vehicles to understand their environment. Relying on the stixel, a compact representation of depth information using thin planar rectangles, the problem of processing huge amounts of depth data in real-time can be solved. In this paper, we present an efficient lossless compression scheme for stixels, which further reduces the data volume by a factor of 3.3863. The predictor of the proposed approach is adapted from the LOCO-I (LOw COmplexity LOssless COmpression for Images) algorithm in the JPEG-LS standard. The compressed stixel data could be sent to the in-vehicle communication bus system for future vehicle applications such as autonomous driving and mixed reality systems.
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Rao, Q., Grünler, C., Hammori, M., Chakraborty, S. (2014). Stixel on the Bus: An Efficient Lossless Compression Scheme for Depth Information in Traffic Scenarios. In: Gurrin, C., Hopfgartner, F., Hurst, W., Johansen, H., Lee, H., O’Connor, N. (eds) MultiMedia Modeling. MMM 2014. Lecture Notes in Computer Science, vol 8325. Springer, Cham. https://doi.org/10.1007/978-3-319-04114-8_48
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DOI: https://doi.org/10.1007/978-3-319-04114-8_48
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