Abstract
Advanced Driver Assistance System (ADAS) is becoming more and more popular and increasing its importance in a car with the advancement in electronics and computer engineering that provides key enabling technologies for such a system. Among others, vision is one of the most important technologies since the current practice of automotive driving is mostly, if not entirely, based on vision. This chapter discusses architectural issues to be considered when designing Systems-on-a-Chip (SoC) for automobile vision system. Various existing architectures are introduced together with some analysis and comparison.
Keywords
- Support Vector Machine
- Support Vector Machine Classifier
- Stereo Image
- Stereo Vision
- Pedestrian Detection
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Kim, K., Choi, K. (2014). SoC Architecture for Automobile Vision System. In: Kim, J., Shin, H. (eds) Algorithm & SoC Design for Automotive Vision Systems. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9075-8_7
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DOI: https://doi.org/10.1007/978-94-017-9075-8_7
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