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Most multi-camera systems assume a well structured environment to detect and match objects across cameras. Cameras need to be fixed and calibrated. In this work, a novel system is presented to detect and match any objects in a network of uncalibrated fixed ...
We propose a method to compute scale invariant features in omnidirectional images. We present a formulation based on Riemannian geometry for the definition of differential operators on non-Euclidian manifolds that describe the mirror and lens structure in ...
We propose a novel 3D tracking method that supports several hundreds of pre-trained potential planar targets without losing real-time performance. This goes well beyond the state-of-the-art, and to reach this level of performances, two threads run in paral ...
This thesis presents an algorithm for face tracking in video sequences. We investigate the application of affine invariant, local features for face tracking under random poses and expressions. In order to capture as much as possible of the facial variabili ...
The sliding window approach is the most widely used technique to detect faces in an image. Usually a classifier is applied on a regular grid and to speed up the scanning, the grid spacing is increased, which increases the number of miss detections. In this ...
SIFT-like local feature descriptors are ubiquitously employed in such computer vision applications as content-based retrieval, video analysis, copy detection, object recognition, photo-tourism and 3D reconstruction. Feature descriptors can be designed to b ...
Most of the multi-camera systems assume a well structured environment to detect and match objects across cameras. Cameras need to be fixed and calibrated. In this work, a novel system is presented to detect and match any objects in a network of uncalibrate ...
We present a new descriptor and feature matching solution for omnidirectional images. The descriptor builds on the log-polar planar descriptors, but adapts to the specific geometry and non-uniform sampling density of spherical images. We further propose a ...
In this paper, we consider the problem of speaker verification as a two-class object detection problem in computer vision, but the object instances are 1-D short-time spectral vectors obtained from the speech signal. More precisely, we investigate the gene ...
We present a fast method to detect humans from stationary surveillance videos. Traditional approaches exploit background subtraction as an attentive filter, by applying the still image detectors only on foreground regions. This doesn't take into account th ...
