Efficient lossless compression for depth information in traffic scenarios

Modern day automotive features (e.g., in-vehicle augmented reality) require a depth of the environment as the input source. It is important that depth data can be transferred from one processing unit to another in a car. About 10 years ago, Stixel has been introduced as a mid-level representation of...

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Bibliographic Details
Published in:Multimedia systems 2019-08, Vol.25 (4), p.293-306
Main Authors: Rao, Qing, Chakraborty, Samarjit
Format: Article
Language:English
Subjects:
Algorithms
Augmented reality
Automobile industry
Automotive engineering
Bandwidths
Communications systems
Compression tests
Computer Communication Networks
Computer Graphics
Computer Science
Controller area network
Cryptology
Data Storage Representation
In vehicle
Operating Systems
Regular Paper
Representations
Traffic information
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Summary:Modern day automotive features (e.g., in-vehicle augmented reality) require a depth of the environment as the input source. It is important that depth data can be transferred from one processing unit to another in a car. About 10 years ago, Stixel has been introduced as a mid-level representation of depth maps (disparities) which reduces the data volume thereof significantly. Since then, Stixel has been extensively researched and is nowadays a seriously considered solution for series production cars. Nevertheless, even after using a Stixel representation, the depth data can hardly fit into a low- or medium-bandwidth in-vehicle communication system, e.g., via a CAN bus. Hence, the cost-sensitive automotive industry is still seeking new solutions for the transmission of depth information using in-vehicle communication buses. In this paper, we present an efficient lossless compression scheme for Stixels as a potential solution to this problem. Our proposed algorithm removes both spatial and temporal redundancies in Stixels through a combination of predictive modeling and entropy coding. Evaluation shows that it outperforms general purpose compression schemes, e.g., zlib, by more than 60 % in space savings. More importantly, we prove that using the proposed Stixel compression, depth information could be transmitted through a less expensive CAN bus, whereas a much more expensive FlexRay bus is needed otherwise. We believe that this finding has great relevance for the automotive industry.
ISSN:0942-4962
1432-1882
DOI:10.1007/s00530-019-00605-z