TY - GEN
T1 - Stixel on the bus
T2 - 20th Anniversary International Conference on MultiMedia Modeling, MMM 2014
AU - Rao, Qing
AU - Grünler, Christian
AU - Hammori, Markus
AU - Chakraborty, Samarjit
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
KW - LOCO-I
KW - lossless compression
KW - stixel
UR - https://www.scopus.com/pages/publications/84893436329
U2 - 10.1007/978-3-319-04114-8_48
DO - 10.1007/978-3-319-04114-8_48
M3 - Conference contribution
AN - SCOPUS:84893436329
SN - 9783319041131
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 568
EP - 579
BT - MultiMedia Modeling - 20th Anniversary International Conference, MMM 2014, Proceedings
Y2 - 6 January 2014 through 10 January 2014
ER -