Readings in computer vision: issues, problems, principles, and paradigms
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
An experiment in linguistic synthesis with a fuzzy logic controller
International Journal of Human-Computer Studies - Special issue: 1969-1999, the 30th anniversary
Image Parsing: Unifying Segmentation, Detection, and Recognition
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Efficient Graph-Based Image Segmentation
International Journal of Computer Vision
Efficient Belief Propagation for Early Vision
International Journal of Computer Vision
International Journal of Computer Vision
Object Recognition by Integrating Multiple Image Segmentations
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Segmentation and Recognition Using Structure from Motion Point Clouds
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
International Journal of Computer Vision
LIDAR and vision-based pedestrian detection system
Journal of Field Robotics
Belief Propagation Implementation Using CUDA on an NVIDIA GTX 280
AI '09 Proceedings of the 22nd Australasian Joint Conference on Advances in Artificial Intelligence
Probabilistic Graphical Models: Principles and Techniques - Adaptive Computation and Machine Learning
What, where and how many? combining object detectors and CRFs
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Semantic segmentation of urban scenes using dense depth maps
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Superparsing: scalable nonparametric image parsing with superpixels
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Nonparametric Scene Parsing via Label Transfer
IEEE Transactions on Pattern Analysis and Machine Intelligence
Are we ready for autonomous driving? The KITTI vision benchmark suite
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Pedestrian detection at 100 frames per second
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Monocular Visual Scene Understanding: Understanding Multi-Object Traffic Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Fusion of information gathered from multiple sources is essential to build a comprehensive situation picture for autonomous ground vehicles. In this paper, an approach which performs scene parsing and data fusion for a 3D-LIDAR scanner (Velodyne HDL-64E) and a video camera is described. First of all, a geometry segmentation algorithm is proposed for detection of obstacles and ground areas from data collected by the Velodyne scanner. Then, corresponding image collected by the video camera is classified patch by patch into more detailed categories. After that, parsing result of each frame is obtained by fusing result of Velodyne data and that of image using the fuzzy logic inference framework. Finally, parsing results of consecutive frames are smoothed by the Markov random field based temporal fusion method. The proposed approach has been evaluated with datasets collected by our autonomous ground vehicle testbed in both rural and urban areas. The fused results are more reliable than that acquired via analysis of only images or Velodyne data.