Detecting runways in complex airport scenes
Computer Vision, Graphics, and Image Processing
An optimization framework for feature extraction
Machine Vision and Applications
Theoretical Aspects of Gray-Level Morphology
IEEE Transactions on Pattern Analysis and Machine Intelligence
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ACM Computing Surveys (CSUR)
Connected filtering and segmentation using component trees
Computer Vision and Image Understanding
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Use of the Hough transformation to detect lines and curves in pictures
Communications of the ACM
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Extraction of Generic House Roofs from High Resolution Aerial Imagery
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 4 - Volume 4
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Rectangle Detection based on a Windowed Hough Transform
SIBGRAPI '04 Proceedings of the Computer Graphics and Image Processing, XVII Brazilian Symposium
3D Segmentation by Maximally Stable Volumes (MSVs)
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Airfield Runway Detection from Synthetic Aperture Radar Image
CISP '08 Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04
Pattern Recognition
Rule-Based Interpretation of Aerial Imagery
IEEE Transactions on Pattern Analysis and Machine Intelligence
Antiextensive connected operators for image and sequence processing
IEEE Transactions on Image Processing
Building the Component Tree in Quasi-Linear Time
IEEE Transactions on Image Processing
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We propose a novel approach to the real-time landing site detection and assessment in unconstrained man-made environments using passive sensors. Because this task must be performed in a few seconds or less, existing methods are often limited to simple local intensity and edge variation cues. By contrast, we show how to efficiently take into account the potential sites' global shape, which is a critical cue in man-made scenes. Our method relies on a new segmentation algorithm and shape regularity measure to look for polygonal regions in video sequences. In this way, we enforce both temporal consistency and geometric regularity, resulting in very reliable and consistent detections. We demonstrate our approach for the detection of landable sites such as rural fields, building rooftops and runways from color and infrared monocular sequences significantly outperforming the state-of-the-art.