Titlebook: Computer Vision - ECCV 2008; 10th European Confer David Forsyth,Philip Torr,Andrew Zisserman Conference proceedings 2008 Springer-Verlag Be

A简洁的

Anisotropic Geodesics for Perceptual Grouping and Domain Meshingsolve two important problems encountered in computer vision and graphics. The first problem studied is perceptual grouping which is a curve reconstruction problem where one should complete in a meaningful way a sparse set of noisy curves. From this latter curves, our grouping algorithm first designs

乞丐

Control-Group

Compressive Sensing for Background Subtractiona signal can be reconstructed from a small set of random projections, provided that the signal is sparse in some basis, e.g., wavelets. In this paper, we describe a method to directly recover background subtracted images using CS and discuss its applications in some communication constrained multi-c

Lobotomy

Linear Time Maximally Stable Extremal Regionskes use of a union-find data structure and takes quasi-linear time in the number of pixels. The new algorithm provides exactly identical results in true worst-case linear time. Moreover, the new algorithm uses significantly less memory and has better cache-locality, resulting in faster execution. Ou

semiskilled

Efficient Edge-Based Methods for Estimating Manhattan Frames in Urban Imagery-called “Manhattan World” assumption [1,2]. While the problem has received considerable attention in recent years, it is unclear how current methods stack up in terms of accuracy and efficiency, and how they might best be improved. It is often argued that it is best to base estimation on all pixels

情节剧

Multiple Component Learning for Object Detectioning rigid objects, achieving very low false positives rates. The field has also seen a resurgence of part-based recognition methods, with impressive results on highly articulated, diverse object categories. In this paper we propose a discriminative learning approach for detection that is inspired by

coagulation

瘙痒

Fast and Accurate Rotation Estimation on the 2-Sphere without Correspondencesimate rotation angles of arbitrary size and resolution. The method is able to achieve great accuracy even for very low spherical harmonic expansions of the input signals without using correspondences or any other kind of a priori information. The rotation parameters are computed analytically without

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围巾