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REN, PRISACARIU,REID: REGRESSING LOCAL TO GLOBAL SHAPE 1 Regressing Local to Global Shape Properties for Online Segmentation and Tracking

by Carl Yuheng Ren, Victor Adrian Prisacariu, Ian Reid
"... We propose a regression based learning framework that learns a set of shapes online, which can then be used to recover occluded object shapes. We represent shapes using their 2D discrete cosine transforms, and the key insight we propose is to regress low frequency harmonics, which represent the glob ..."
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the global properties of the shape, from high frequency harmonics, that encode the details of the object’s shape. We learn the regression model using Locally Weighted Projection Regression (LWPR) which expedites online, incremental learning. After sufficient observation of a set of unoccluded shapes

Coarseto-fine segmentation and tracking using Sobolev active contours

by Ganesh Sundaramoorthi, Anthony Yezzi, Andrea C. Mennucci - IEEE TPAMI , 2008
"... Recently proposed Sobolev active contours introduced a new paradigm for minimizing energies defined on curves by changing the traditional cost of perturbing a curve and thereby redefining gradients associated to these energies. Sobolev active contours evolve more globally and are less attracted to ..."
Abstract - Cited by 18 (5 self) - Add to MetaCart
to certain intermediate local minima than traditional active contours, and it is based on a well-structured Riemannian metric, which is important for shape analysis and shape priors. In this paper, we analyze Sobolev active contours using scale-space analysis in order to understand their evolution across

Brownian Strings: Segmenting Images with Stochastically Deformable Models

by Robert P. Grzeszczuk, David N. Levin , 1995
"... Abstract—This paper describes an image segmentation technique in which an arbitrarily shaped contour was deformed stochastically until it fitted around an object of interest. The evolution of the contour was controlled by a simulated annealing process which caused the contour to settle into the glob ..."
Abstract - Cited by 34 (0 self) - Add to MetaCart
into the global minimum of an image-derived “energy ” function. The nonparametric energy function was derived from the statistical properties of previously segmented images, thereby incorporating prior experience. Since the method was based on a state space search for the contour with the best global properties

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 1 Coarse-to-Fine Segmentation and Tracking Using Sobolev Active Contours

by Ganesh Sundaramoorthi, Anthony Yezzi, Senior Member Ieee, Andrea C. Mennucci
"... Abstract — Recently proposed Sobolev active contours introduced a new paradigm for minimizing energies defined on curves by changing the traditional cost of perturbing a curve and thereby redefining their gradients. Sobolev active contours evolve more globally and are less attracted to certain inter ..."
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intermediate local minima than traditional active contours, and it is based on a well-structured Riemannian metric, which is important for shape analysis and shape priors. In this paper, we analyze Sobolev active contours using scale-space analysis in order to understand their evolution across different scales

Pose-Configurable Generic Tracking of Elongated Objects

by Daniel Wesierski, Patrick Horain
"... Elongated objects have various shapes and can shift, ro-tate, change scale, and be rigid or deform by flexing, artic-ulating, and vibrating, with examples as varied as a glass bottle, a robotic arm, a surgical suture, a finger pair, a tram, and a guitar string. This generally makes tracking of poses ..."
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assembly of segments of mul-tiple parts that are arranged under a hierarchy of tailored spatio-temporal constraints. In this hierarchy, segments can rescale independently while their elasticity is controlled with global orientations and local distances. While the trend in tracking is to design complex

Perspective An Online Bioinformatics Curriculum

by David B. Searls
"... Abstract: Online learning initia-tives over the past decade have become increasingly comprehen-sive in their selection of courses and sophisticated in their presen-tation, culminating in the recent announcement of a number of consortium and startup activities that promise to make a university educat ..."
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Abstract: Online learning initia-tives over the past decade have become increasingly comprehen-sive in their selection of courses and sophisticated in their presen-tation, culminating in the recent announcement of a number of consortium and startup activities that promise to make a university

Active Mask Framework for Segmentation of Fluorescence Microscope Images

by Gowri Srinivasa, Advisor Prof, Prof Matthew, C. Fickus, Prof Adam, D. Linstedt, Prof Robert, F. Murphy
"... m]]l]]s¶D]]¿÷mB]iv]b]oD]m¶¨]iv]§]iv]r]j]t¿rv]]irj]]t]]m] / | ap]]r¿]ÎNy]s¶D]]mb¶r]ix} Û]Ix]]rd]mb]} p—N]t]o%ism] in]ty]m] / || Û]Is]¡uÎc]rN]]riv]nd]p]*N]m]st¶ I always bow to Śri ̄ Śāradāmbā, the limitless ocean of the nectar of compassion, who bears a rosary, a vessel of nectar, the symbol of ..."
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of knowledge and a book in Her lotus hands. Dedicated to the Lotus Feet of the revered Sadguru. This thesis presents a new active mask (AM) framework and an algorithm for segmenta-tion of digital images, particularly those of punctate patterns from fluorescence microscopy. Fluorescence microscopy has greatly

Learning Probabilistic Deformation Models from Image Sequences

by Charles Kervrann , 1998
"... In this paper, we present an approach for an unsupervised learning of probabilistic deformation modes of 2D moving objects from image sequences. The object representation relies on a statistical description of global and local deformations applied to an a priori prototype shape. The optimal bayes ..."
Abstract - Cited by 3 (0 self) - Add to MetaCart
In this paper, we present an approach for an unsupervised learning of probabilistic deformation modes of 2D moving objects from image sequences. The object representation relies on a statistical description of global and local deformations applied to an a priori prototype shape. The optimal

unknown title

by unknown authors
"... ABSTRACT: In Computer vision, image segmentation is the process of partitioning a digital image into multiple segments, Human segmentation in photo images is a challenging and important problem. As computer vision researchers have increased attention in segmenting human from a given input image or ..."
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Fields and global shape priors to estimate segmentations and pose simultaneously is also proposed. Some utilized pose-specific conditional random and stick figures for segmentation, as well as pose estimation of humans within a Bayesian framework, which has been success-fully used in 3-D human pose

unknown title

by unknown authors
"... The role of segmentation and investor recognition through the lens of cross-listing activity∗ Francesca Carrieri†, Xavier Mouchette‡, Aline Muller§ We focus on the price effects occurring around cross-listing and research the impact of the sequencing of cross-listing, defined as the cumulative numbe ..."
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The role of segmentation and investor recognition through the lens of cross-listing activity∗ Francesca Carrieri†, Xavier Mouchette‡, Aline Muller§ We focus on the price effects occurring around cross-listing and research the impact of the sequencing of cross-listing, defined as the cumulative
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