Contextual Priming for Object Detection
International Journal of Computer Vision
A Video-Based Support System for Nighttime Navigation in Semi-Structured Environments
SIBGRAPI '04 Proceedings of the Computer Graphics and Image Processing, XVII Brazilian Symposium
Dynamic speedometer: dashboard redesign to discourage drivers from speeding
CHI '05 Extended Abstracts on Human Factors in Computing Systems
CarTel: a distributed mobile sensor computing system
Proceedings of the 4th international conference on Embedded networked sensor systems
Journal of Intelligent and Robotic Systems
A survey on context-aware systems
International Journal of Ad Hoc and Ubiquitous Computing
The pothole patrol: using a mobile sensor network for road surface monitoring
Proceedings of the 6th international conference on Mobile systems, applications, and services
DGS: Driving Guidance System Based on Wireless Sensor Network
AINAW '08 Proceedings of the 22nd International Conference on Advanced Information Networking and Applications - Workshops
Vehicle speed detection from a single motion blurred image
Image and Vision Computing
Driver Fatigue Detection Based on Eye Tracking
ICETET '08 Proceedings of the 2008 First International Conference on Emerging Trends in Engineering and Technology
Vehicle Speed Measurement Based on Video Images
ICICIC '08 Proceedings of the 2008 3rd International Conference on Innovative Computing Information and Control
Nericell: rich monitoring of road and traffic conditions using mobile smartphones
Proceedings of the 6th ACM conference on Embedded network sensor systems
DICTA '08 Proceedings of the 2008 Digital Image Computing: Techniques and Applications
An Effective and Fast Lane Detection Algorithm
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
Continuous Range Search Query Processing in Mobile Navigation
ICPADS '08 Proceedings of the 2008 14th IEEE International Conference on Parallel and Distributed Systems
Bird's-eye view vision system for vehicle surrounding monitoring
RobVis'08 Proceedings of the 2nd international conference on Robot vision
Robust video communication over an urban VANET
Mobile Information Systems
Constrained range search query processing on road networks
Concurrency and Computation: Practice & Experience
Event sharing in vehicular networks using geographic vectors and maps
Mobile Information Systems
Voronoi-based multi-level range search in mobile navigation
Multimedia Tools and Applications
Determining driver visual attention with one camera
IEEE Transactions on Intelligent Transportation Systems
Video-based lane estimation and tracking for driver assistance: survey, system, and evaluation
IEEE Transactions on Intelligent Transportation Systems
Real-time system for monitoring driver vigilance
IEEE Transactions on Intelligent Transportation Systems
Looking-In and Looking-Out of a Vehicle: Computer-Vision-Based Enhanced Vehicle Safety
IEEE Transactions on Intelligent Transportation Systems
A Low-Cost Pedestrian-Detection System With a Single Optical Camera
IEEE Transactions on Intelligent Transportation Systems
Integrated context-aware driver assistance system architecture
Mobile Information Systems
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Road accidents cause a great loss to human lives and assets. Most of the accidents occur due to human errors, such as bad awareness, distraction, drowsiness, low training, and fatigue. Advanced driver assistance system (ADAS) can reduce the human errors by keeping an eye on the driving environment and warning a driver to the upcoming danger. However, these systems come only with modern luxury cars because of their high cost and complexity due to several sensors employed. Therefore, camera-based ADAS are becoming an option due to their lower cost, higher availability, numerous applications and ability to combine with other systems. Targeting at designing a camera-based ADAS, we have conducted an ethnographic study of drivers to know what information about the driving environment would be useful in preventing accidents. It turned out that information on speed, distance, relative position, direction, and size and type of the nearby objects would be useful and enough for implementing most of the ADAS functions. Several camera-based techniques are available for capturing the required information. We propose a novel design of an integrated camera-based ADAS that puts technologies--such as five ordinary CMOS image sensors, a digital image processor, and a thin display--into a smart system to offer a dozen advanced driver assistance functions. A basic prototype is also implemented using MATLAB. Our design and the prototype testify that all the required technologies are now available for implementing a full-fledged camera-based ADAS.