Keypoint Recognition using Random Forests and Random Ferns
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Change detection generally is the difference between images. The differences or changes could be due to moving objects or a variation of illumination. In general the goal is to extract only changes due to moving object that occur int eh scene, and to ignor ...
When comparing different methods for face detection or localization, one realizes that just simply comparing the reported results is misleading as, even if the results are reported on the same dataset, different authors have different views of what a corre ...
Change detection is a temporal segmentation tool aiming at identifying changes in image sets or image sequences at two different times. Many change detection algorithms have been proposed over the past decade for the generation of video objects in a wide r ...
Humans have the ability to learn. Having seen an object we can recognise it later. We can do this because our nervous system uses an efficient and robust visual processing and capabilities to learn from sensory input. On the other hand, designing algorithm ...
When comparing different methods for face detection or localization, one realizes that just simply comparing the reported results is misleading as, even if the results are reported on the same dataset, different authors have different views of what a corre ...
International Society for Magnetic Resonance in Medicine2004
This paper introduces a two-steps adaptive generalized Hough transform (GHT) for the detection of non-analytic objects undergoing weak affine transformations in images. The first step of our algorithm coarsely locates the region of interest with a GHT for ...
In this paper, we show that in a multi-camera context, we can effectively handle occlusions at each time frame independently, even when the only available data comes from the binary output of a fairly primitive motion detector. We start from occupancy prob ...
The performance of face verification systems has steadily improved over the last few years. State-of-the-art methods use the projection of the gray-scale face image into a Linear Discriminant subspace as input of a classifier such as Support Vector Machine ...