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 and use this local cooccurring pattern to detect objects from aerial images is presented. This methodis a semi-automatic method, which allows users to determine various objects of interest to be detected via a simple clicking on any object of the same class in the image. Features including colour features and edge-based shape features of the selected object are then 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 e®ectively reducing the labour work in finding man-made objects of interest from aerial images.
|Title of host publication||9th international conference, VISUAL 2007, Shanghai, China, June 28-29, 2007|
|Subtitle of host publication||revised selected papers|
|Place of Publication||Berlin / Heidelberg, Germany|
|Number of pages||12|
|Publication status||Published - 2007|
Jia, W., Tien, D., He, X., Hope, B. A., & Wu, Q. (2007). Applying Local Cooccurring Patterns for Object Detection from Aerial Images. In 9th international conference, VISUAL 2007, Shanghai, China, June 28-29, 2007: revised selected papers (1 ed., Vol. 4781/2007, pp. 478-489). Springer. https://doi.org/10.1007/978-3-540-76414-4_47