Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Active Testing Model for Tracking Roads in Satellite Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fundamental Limits of Bayesian Inference: Order Parameters and Phase Transitions for Road Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple view geometry in computer vision
Multiple view geometry in computer vision
Normalized Cuts and Image Segmentation
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Mean Shift Analysis and Applications
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Detecting Pedestrians Using Patterns of Motion and Appearance
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Efficient Graph-Based Image Segmentation
International Journal of Computer Vision
Geometric Context from a Single Image
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Recognition and Segmentation of Scene Content using Region-Based Classification
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Recovering Surface Layout from an Image
International Journal of Computer Vision
Recovering human body configurations: combining segmentation and recognition
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Turbopixel segmentation using Eigen-images
IEEE Transactions on Image Processing
Sub-sampling: Real-time vision for micro air vehicles
Robotics and Autonomous Systems
| Hi-index | 0.00 |
We introduce a framework for object detection and tracking in video of natural outdoor scenes based on fast per-frame segmentations using Felzenszwalb's graph-based algorithm. Region boundaries obtained at multiple scales are first temporally filtered to detect stable structures to be considered as object hypotheses. Depending on object type, these are then classified using a priori appearance characteristics such as color and texture and geometric attributes derived from the Hough transform. We describe preliminary results on image sequences taken from low-flying aircraft in which object categories are relevant to UAVs, consisting of sky, ground, and navigationally-useful ground features such as roads and pipelines.