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Road Scene Content Analysis for Driver Assistance and Autonomous Driving

Altun, Melih
http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1418665048

Abstract Details

2015, Doctor of Philosophy (PhD), Ohio University, Electrical Engineering & Computer Science (Engineering and Technology).
This research aims to develop a vision based driver assistance system that achieves scene awareness using video frames obtained from a dashboard camera. A saliency image map is formed with features pertinent to the driving scene. This saliency map, based on contour and motion sensitive human visual perception, is devised by extracting spatial, spectral and temporal information from the input frames and applying data fusion. Fusion output contains high level descriptors for segment boundaries and non-stationary objects. Following the segmentation and foreground object detection stage, an adaptive Bayesian learning framework classifies road surface regions and the detected foreground objects are tracked via Kalman filtering. In turn, this oversees potential collisions with the tracked objects. Furthermore, the vehicle path is used in conjunction with the extracted road information to detect deviations from the road surfaces. The system forms an augmented reality output in which video frames are context enhanced with the object tracking and road surface information. The proposed scene driven vision system improves the driver’s situational awareness by enabling adaptive road surface classification, object tracking and collision estimation. As experimental results demonstrate, context aware low level to high level information fusion based on human vision model produces superior segmentation, tracking and classification results that lead to high level abstraction of driving scene.
Mehmet Celenk, PhD (Advisor)
149 p.
Computer Science; Electrical Engineering
Road scene; content analysis; saliency map; entropy driven context-feature fusion

Recommended Citations

Citations

  • Altun, M. (2015). Road Scene Content Analysis for Driver Assistance and Autonomous Driving [Doctoral dissertation, Ohio University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1418665048

    APA Style (7th edition)

  • Altun, Melih. Road Scene Content Analysis for Driver Assistance and Autonomous Driving. 2015. Ohio University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1418665048.

    MLA Style (8th edition)

  • Altun, Melih. "Road Scene Content Analysis for Driver Assistance and Autonomous Driving." Doctoral dissertation, Ohio University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1418665048

    Chicago Manual of Style (17th edition)

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This open access ETD is published by Ohio University and OhioLINK.