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논문 기본 정보

자료유형
학술저널
저자정보
(Seoul National University of Science and Technology) (Seoul National University of Science and Technology)
저널정보
대한전자공학회 IEIE Transactions on Smart Processing & Computing IEIE Transactions on Smart Processing & Computing Vol.11 No.2
발행연도
수록면
105 - 111 (7page)

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초록· 키워드

This work addresses the task of locating regions that are more crucial for safe driving than other areas on roads. It could be utilized to improve the efficiency and safety of autonomous driving vehicles or robots and could also be useful for human drivers when employed in driver-assistance systems. To achieve robust and accurate attention prediction, we propose a multiscale color and motion-based attention prediction network. The network consists of three components where each processes multi-scaled color images, uses multi-scaled motion information, and merges the outputs of the two streams, respectively. The proposed network is guided to utilize the movement of objects/people as well as the type/location of things/stuff. We demonstrate the effectiveness of the proposed system by experimenting with an actual driving dataset. The experimental results show that the proposed framework outperforms previous works.
#Visual attention estimation #Intelligent transportation system #Convolutional neural networks #Saliency estimation #Video-based
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목차

  1. Abstract
  2. 1. Introduction
  3. 2. Related Works
  4. 3. Proposed Method
  5. 4. Experiments and Results
  6. 5. Conclusion
  7. References

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