Vision-Based Road Detection in Automotive Systems: A Real-Time Expectation-Driven Approach
<|reference_start|>Vision-Based Road Detection in Automotive Systems: A Real-Time Expectation-Driven Approach: The main aim of this work is the development of a vision-based road detection system fast enough to cope with the difficult real-time constraints imposed by moving vehicle applications. The hardware platform, a special-purpose massively parallel system, has been chosen to minimize system production and operational costs. This paper presents a novel approach to expectation-driven low-level image segmentation, which can be mapped naturally onto mesh-connected massively parallel SIMD architectures capable of handling hierarchical data structures. The input image is assumed to contain a distorted version of a given template; a multiresolution stretching process is used to reshape the original template in accordance with the acquired image content, minimizing a potential function. The distorted template is the process output.<|reference_end|>
@article{broggi1995vision-based,
    title={Vision-Based Road Detection in Automotive Systems: A Real-Time
  Expectation-Driven Approach},
    author={A. Broggi, S. Berte},
    journal={Journal of Artificial Intelligence Research, Vol 3, (1995),
  325-348},
    year={1995},
    archivePrefix={arXiv},
    eprint={cs/9512102},
    primaryClass={cs.AI}
}