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Adaptive Parameter Optimization for Real-time Tracking
(IEEE, 2007-10)
Adaptation of a tracking procedure combined in a common way with a Kalman filter is formulated as an constrained optimization problem, where a trade-off between precision and loss-of-lock probability is explicitly taken ...
Colour-Based Object Recognition for Video Annotation
(IEEE, 2002)
We propose a colour-based object recognition method for video annotation. The semantic gap between image measurements and symbolic labelling is bridged by assuming the existence of objects whose appearance can be associated ...
Local Affine Frames for Wide-Baseline Stereo
(IEEE, 2002)
A novel procedure for establishing wide-baseline correspondence is introduced. Tentative correspondences are established by matching photometrically normalised colour measurements represented in a local affine frame. The ...
Efficient Sequential Correspondence Selection by Cosegmentation
(IEEE, 2008-06)
In many retrieval, object recognition and wide baseline stereo methods, correspondences of interest points are established possibly sublinearly by matching a compact descriptor such as SIFT. We show that a subsequent ...
Geometric min-Hashing: Finding a (Thick) Needle in a Haystack
(IEEE, 2009-06)
We propose a novel hashing scheme for image retrieval, clustering and automatic object discovery. Unlike commonly used bag-of-words approaches, the spatial extent of image features is exploited in our method. The geometric ...
A voting strategy for visual ego-motion from stereo
(IEEE, 2010-06)
We present a procedure for egomotion estimation from visual input of a stereo pair of video cameras. The 3D egomotion problem, which has six degrees of freedom in general, is simplified to four dimensions and further ...
Large-Scale Discovery of Spatially Related Images
(IEEE, 2010-02)
We propose a randomized data mining method that finds clusters of spatially overlapping images. The core of the method relies on the min-Hash algorithm for fast detection of pairs of images with spatial overlap, the so-called ...
Unsupervised Discovery of Co-occurrence in Sparse High Dimensional Data
(IEEE, 2010-06)
An efficient min-Hash based algorithm for discovery of dependencies in sparse high-dimensional data is presented. The dependencies are represented by sets of features co-occurring with high probability and are called ...
Tracking by an Optimal Sequence of Linear Predictors
(IEEE, 2009-04)
We propose a learning approach to tracking explicitly minimizing the computational complexity of the tracking process subject to user-defined probability of failure (loss-of-lock) and precision. The tracker is formed by a ...
Fast Detection of Multiple Textureless 3-D Objects
(Springer, 2013)
We propose a fast edge-based approach for detection and approximate pose estimation of multiple textureless objects in a single image. The objects are trained from a set of edge maps, each showing one object in one pose. ...