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In this paper, we describe how an effective vanishing point detector can be applied to photogrammetry when only a single view of an architectural environment is available. Our method performs automatic segment clustering in projective space - a direct transformation from the image space - instead of the traditional bounded accumulator space. Experiments on real images show the effectiveness of the...
Hyperspectral change detection has been proved to be a promising technique for detecting indiscernible targets in different background. However, in the case of dense industrial and urban areas the complexity of the terrain and the multi-temporal images, which include positional deviation, radiant and atmospheric variation, shadows and spatial structure alteration, severely affects the automation of...
This paper present an efficient real time rectangle speed limit sign recognition system. The system design considers computation load and hardware resources for driver assistant system. First multi-scale overlapping LBP features are used to train AdaBoost cascade classifier for speed limit sign object detection. Then a simple linear prediction method is used to do tracking task. At the recognition...
Methods developed for image annotation usually make use of region clustering algorithms. Visual codebooks are generated from the region clusters of low level features. These codebooks are then, matched with the words of the text document related to the image, in various ways. In this paper, we supervise the clustering process by using three types of side information. The first one is the topic probability...
Many anomaly detection methods, depending on various parameters, have been proposed in literature. Given the diversity of available anomaly detectors, froman operational viewpoint it is interesting to determine an efficient strategy to find the best suited detector for a given application. This is not obvious, especially in scenes with a highly structured background. The work presented here proposes...
In content-based image retrieval, how to representation of local properties in an image is one of the most active research issues. In certain circumstance, however, users concern more about objects of their interest and only wish to retrieve images containing relevant objects, while ignoring irrelevant image areas (such as the background). Previous work on represent of local properties normally requires...
Interest point detection is an established method to select relevent image regions. Such techniques use features like corners or edges, which are known to indicate regions likely to hold patterns of interest. Selection of such regions increases processing efficiency. For the recognition of motion, however, such context-free methods are still very rare. Though there are numerous methods to find space-time...
The objective of this work is the detection of object classes. An improved method is used for object detection and segmentation in real-world multiple-object scenes. It has two stages. In the first stage this method develops a novel technique to extract class-discriminative boundary fragments and the texture features near the boundary, and then boosting is used to select discriminative boundary fragments...
The objective of this work is the detection of object classes. An improved method is used for object detection and segmentation in real-world multiple-object scenes. It has two stages. In the first stage this method develops a novel technique to extract class-discriminative boundary fragments, and then boosting is used to select discriminative boundary fragments (weak detectors) toform a strong "boundary-fragment-model"...
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