Digital Color Management: Encoding Solutions
Digital Color Management: Encoding Solutions
Mean Shift Analysis and Applications
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Bilateral Filtering for Gray and Color Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
State of the art on automatic road extraction for GIS update: a novel classification
Pattern Recognition Letters
Refined Gaussian Weighted Histogram Intersection and Its Application in Number Plate Categorization
CGIV '06 Proceedings of the International Conference on Computer Graphics, Imaging and Visualisation
Gaussian Weighted Histogram Intersection for License Plate Classification
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Discovering the Local Co-occurring Patterns in Visual Categorization
AVSS '06 Proceedings of the IEEE International Conference on Video and Signal Based Surveillance
A fast approximation of the bilateral filter using a signal processing approach
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
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Developing a spatial searching tool to enhance the search capabilities of large spatial repositories for Geographical Information System (GIS) update has attracted more and more attention. Typically, objects to be detected are represented by many local features or local parts. Testing images are processed by extracting local features which are then matched with the object's model image. Most existing work that uses local features assumes that each of the local features is independent to each other. However, in many cases, this is not true. In this paper, a method of applying the local cooccurring patterns to disclose the cooccurring relationships between local features for object detection is presented. Features including colour features and edge-based shape features of the interested object are collected. To reveal the cooccurring patterns among multiple local features, a colour cooccurrence histogram is constructed and used to search objects of interest from target images. The method is demonstrated in detecting swimming pools from aerial images. Our experimental results show the feasibility of using this method for effectively reducing the labour work in finding man-made objects of interest from aerial images.