Road following using vannishing points
Computer Vision, Graphics, and Image Processing
A Deformable Template Approach to Detecting Straight Edges in Radar Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
A machine vision system for lane-departure detection
Computer Vision and Image Understanding
Circular road signs recognition with soft classifiers
Integrated Computer-Aided Engineering - Artificial Neural Networks
A Fast and Robust Approach to Lane Marking Detection and Lane Tracking
SSIAI '08 Proceedings of the 2008 IEEE Southwest Symposium on Image Analysis and Interpretation
Moving object detection in the H.264/AVC compressed domain for video surveillance applications
Journal of Visual Communication and Image Representation
Vision-based road detection in automotive systems: a real-time expectation-driven approach
Journal of Artificial Intelligence Research
Applying fuzzy method to vision-based lane detection and departure warning system
Expert Systems with Applications: An International Journal
Fast Compressed Domain Motion Detection in H.264 Video Streams for Video Surveillance Applications
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
Real-time moving object segmentation in H.264 compressed domain based on approximate reasoning
International Journal of Approximate Reasoning
Lane following and lane departure using a linear-parabolic model
Image and Vision Computing
A multi-agent system for managing adverse weather situations on the road network
Integrated Computer-Aided Engineering
Lane detection and tracking using a new lane model and distance transform
Machine Vision and Applications
Robust Lane Detection and Tracking in Challenging Scenarios
IEEE Transactions on Intelligent Transportation Systems
Lane detection by orientation and length discrimination
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
GOLD: a parallel real-time stereo vision system for generic obstacle and lane detection
IEEE Transactions on Image Processing
Using adaptive background subtraction into a multi-level model for traffic surveillance
Integrated Computer-Aided Engineering
Detection and classification of road signs for automatic inventory systems using computer vision
Integrated Computer-Aided Engineering
Hi-index | 0.00 |
The detection and localization of road lane marks are relevant to many applications of driving assistance and road traffic surveillance. Usually, these techniques work by processing all the pixels in every image, making the computational cost too high. In these situations, the implementation of real-time detection applications is impossible. Processing the video directly in the compressed domain avoids this limitation because the data rate is much reduced and full decoding of the compressed images is unnecessary. The development of a real-time detection systems then becomes possible, even for resource-limited systems like mobile devices. In this paper an approach to the segmentation and recognition of lane marks using only H264/AVC motion vectors is proposed. A new representation of motion vectors is defined in order to detect efficiently the regions or blobs of interest in complex videos captured by moving cameras. Then, a set of mathematical filters are applied removing progressively the blobs detected, depending on their position in the scene, their size, and their shape; and obtaining finally the regions corresponding to the lane marks. The proposed method shows encouraging results in different road traffic video sequences.