Robust, High-Speed Interest Point Matching for Real-Time Applications
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Feature description for local image patch is widely used in computer vision. While the conventional way to design local descriptor is based on expert experience and knowledge, learning based methods for designing local descriptor become more and more popul ...
Institute of Electrical and Electronics Engineers2014
In many 3-D object-detection and pose-estimation problems, run-time performance is of critical importance. However, there usually is time to train the system. We introduce an approach that takes advantage of this fact by formulating wide-baseline matching ...
Object classification and detection aim at recognizing and localizing objects in real-world images. They are fundamental computer vision problems and a prerequisite for full scene understanding. Their difficulty lies in the large number of possible object ...
Programme doctoral en Informatique, Communications et Information2013
The sliding window approach is the most widely used technique to detect an object from an image. In the past few years, classifiers have been improved in many ways to increase the scanning speed. Apart from the classifier design (such as the cascade), the ...
Object detection is a significant challenge in Computer Vision and has received a lot of attention in the field. One such challenge addressed in this thesis is the detection of polygonal objects, which are prevalent in man-made environments. Shape analysis ...
Medical ultrasonic imaging applications require high quality of images produced in real-time often with limited resources available. Deadlock-freedom and confluency must be guaranteed to insure the correctness of the applications, while feasibility and opt ...
Many algorithms have been proposed to solve the problem of matching feature points in two or more images using geometric assumptions to increase the robustness of the matching. However, these assumptions do not always hold; in particular, few methods addre ...