Results 1  10
of
167
The variable bandwidth meanshift and datadriven scale selection,” in ICCV,
, 2001
"... Abstract We present two solutions for the scale selection problem in computer vision. The first one is completely nonparametric and is based on the the adaptive estimation of the normalized density gradient. Employing the sample point estimator, we define the Variable Bandwidth Mean Shift, prove it ..."
Abstract

Cited by 130 (9 self)
 Add to MetaCart
(Show Context)
Abstract We present two solutions for the scale selection problem in computer vision. The first one is completely nonparametric and is based on the the adaptive estimation of the normalized density gradient. Employing the sample point estimator, we define the Variable Bandwidth Mean Shift, prove its convergence, and show its superiority over the fixed bandwidth procedure. The second technique has a semiparametric nature and imposes a local structure on the data to extract reliable scale information. The local scale of the underlying density is taken as the bandwidth which maximizes the magnitude of the normalized mean shift vector. Both estimators provide practical tools for autonomous image and quasi realtime video analysis and several examples are shown to illustrate their effectiveness. Motivation for Variable Bandwidth The efficacy of Mean Shift analysis has been demonstrated in computer vision problems such as tracking and segmentation in [5, 61. However, one of the limitations of the mean shift procedure as defined in these papers is that it involves the specification of a scale parameter. While results obtained appear satisfactory, when the local characteristics of the feature space differs significantly across data, it is difficult to find an optimal global bandwidth for the mean shift procedure. In this paper we address the issue of locally adapting the bandwidth. We also study an alternative approach for datadriven scale selection which imposes a local structure on the data. The proposed solutions are tested in the framework of quasi realtime video analysis. We review first the intrinsic limitations of the fixed bandwidth density estimation methods. Then, two of the most popular variable bandwidth estimators, the balloon and the sample point, are introduced and their advantages discussed. We conclude the section by showing that, with some precautions, the performance of the sample point estimator is superior to both fixed bandwidth and balloon estimators.
Computing Contour Closure
 In Proc. 4th European Conference on Computer Vision
, 1996
"... . Existing methods for grouping edges on the basis of local smoothness measures fail to compute complete contours in natural images: it appears that a stronger global constraint is required. Motivated by growing evidence that the human visual system exploits contour closure for the purposes of p ..."
Abstract

Cited by 109 (11 self)
 Add to MetaCart
(Show Context)
. Existing methods for grouping edges on the basis of local smoothness measures fail to compute complete contours in natural images: it appears that a stronger global constraint is required. Motivated by growing evidence that the human visual system exploits contour closure for the purposes of perceptual grouping [6, 7, 14, 15, 25], we present an algorithm for computing highly closed bounding contours from images. Unlike previous algorithms [11, 18, 26], no restrictions are placed on the type of structure bounded or its shape. Contours are represented locally by tangent vectors, augmented by image intensity estimates. A Bayesian model is developed for the likelihood that two tangent vectors form contiguous components of the same contour. Based on this model, a sparselyconnected graph is constructed, and the problem of computing closed contours is posed as the computation of shortestpath cycles in this graph. We show that simple tangent cycles can be efficiently computed ...
Ecological statistics of Gestalt laws for the perceptual organization of contours
, 2002
"... Although numerous studies have measured the strength of visual grouping cues for controlled psychophysical stimuli, little is known about the statistical utility of these various cues for natural images. In this study, we conducted eFperiments in which human participants trace perceived contours in ..."
Abstract

Cited by 100 (6 self)
 Add to MetaCart
(Show Context)
Although numerous studies have measured the strength of visual grouping cues for controlled psychophysical stimuli, little is known about the statistical utility of these various cues for natural images. In this study, we conducted eFperiments in which human participants trace perceived contours in natural images. These contours are automatically mapped to seGuences of discrete tangent elements detected in the image. By eFamining relational properties between pairs of successive tangents on these traced curves, and between randomly selected pairs of tangents, we are able to estimate the likelihood distributions reGuired to construct an optimal Bayesian model for contour grouping. We employed this novel methodology to investigate the inferential power of three classical Gestalt cues for contour groupingJ proFimity, good continuation, and luminance similarity. The study yielded a number of important resultsJ K1M these cues, when appropriately defined, are approFimately uncorrelated, suggesting a simple factorial model for statistical inferenceN K2M moderate imagetoimage variation of the statistics indicates the utility of general probabilistic models for perceptual organiQationN KRM these cues differ greatly in their inferential power, proFimity being by far the most powerfulN and KSM statistical modeling of the proFimity cue indicates a scaleinvariant power law in close agreement with prior psychophysics.
Localizing regionbased active contours
 IEEE TRANS. ON IMAGE PROCESSING
, 2008
"... In this paper, we propose a natural framework that allows any regionbased segmentation energy to be reformulated in a local way. We consider local rather than global image statistics and evolve a contour based on local information. Localized contours are capable of segmenting objects with heterog ..."
Abstract

Cited by 77 (3 self)
 Add to MetaCart
In this paper, we propose a natural framework that allows any regionbased segmentation energy to be reformulated in a local way. We consider local rather than global image statistics and evolve a contour based on local information. Localized contours are capable of segmenting objects with heterogeneous feature profiles that would be difficult to capture correctly using a standard global method. The presented technique is versatile enough to be used with any global regionbased active contour energy and instill in it the benefits of localization. We describe this framework and demonstrate the localization of three wellknown energies in order to illustrate how our framework can be applied to any energy. We then compare each localized energy to its global counterpart to show the improvements that can be achieved. Next, an indepth study of the behaviors of these energies in response to the degree of localization is given. Finally, we show results on challenging images to illustrate the robust and accurate segmentations that are possible with this new class of active contour models.
Image Editing in the Contour Domain
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 1998
"... Image editing systems are essentially pixelbased. In this paper we propose a novel method for image editing in which the primitive working unit is not a pixel but an edge. The feasibility of this proposal is suggested by recent work showing that a greyscale image can be accurately represented by i ..."
Abstract

Cited by 65 (3 self)
 Add to MetaCart
(Show Context)
Image editing systems are essentially pixelbased. In this paper we propose a novel method for image editing in which the primitive working unit is not a pixel but an edge. The feasibility of this proposal is suggested by recent work showing that a greyscale image can be accurately represented by its edge map if a suitable edge model and scale selection method are employed [1]. In particular, an efficient algorithm has been reported to invert such an edge representation to yield a highfidelity reconstruction of the original image [2]. We have combined these algorithms together with an efficient method for contour grouping and an intuitive user interface to allow users to perform image editing operations directly in the contour domain. Experimental results suggest that this novel combination of vision algorithms may lead to substantial improvements in the efficiency of certain classes of image editing operations. 1 Introduction The ultimate commercial goal of most computer vision re...
Perceptual blur and ringing metrics: Application to JPEG2000,” Signal Process
 Image Commun
, 2004
"... We present a full and noreference blur metric as well as a fullreference ringing metric. These metrics are based on an analysis of the edges and adjacent regions in an image and have very low computational complexity. As blur and ringing are typical artifacts of wavelet compression, the metrics a ..."
Abstract

Cited by 65 (1 self)
 Add to MetaCart
(Show Context)
We present a full and noreference blur metric as well as a fullreference ringing metric. These metrics are based on an analysis of the edges and adjacent regions in an image and have very low computational complexity. As blur and ringing are typical artifacts of wavelet compression, the metrics are then applied to JPEG2000 coded images. Their perceptual significance is corroborated through a number of subjective experiments. The results show that the proposed metrics perform well over a wide range of image content and distortion levels. Potential applications include source coding optimization and network resource management. r 2003 Elsevier B.V. All rights reserved.
Are Edges Incomplete?
"... . We address the problem of computing a generalpurpose early visual representation that satisfies two criteria. 1) Explicitness: To be more useful than the original pixel array, the representation must take a significant step toward making important image structure explicit. 2) Completeness: To sup ..."
Abstract

Cited by 65 (3 self)
 Add to MetaCart
. We address the problem of computing a generalpurpose early visual representation that satisfies two criteria. 1) Explicitness: To be more useful than the original pixel array, the representation must take a significant step toward making important image structure explicit. 2) Completeness: To support a diverse set of highlevel tasks, the representation must not discard information of potential perceptual relevance. The most prevalent representation in image processing and computer vision that satisfies the completeness criterion is the wavelet code. In this paper, we propose a very different code which represents the location of each edge and the magnitude and blur scale of the underlying intensity change. By making edge structure explicit, we argue that this representation better satisfies the first criterion than do wavelet codes. To address the second criterion, we study the question of how much visual information is lost in the representation. We report a novel method for inver...
N.: Visual sensitivity, blur and the sources of variability in the amplitude spectra of natural images. Vision Research 37
, 1997
"... A number of researchers have suggested that in order to understand the response properties of cells in the visual pathway, we must consider the statistical structure of the natural environment. In this paper, we focus on one aspect of that structure, namely, the correlational structure which is desc ..."
Abstract

Cited by 62 (3 self)
 Add to MetaCart
(Show Context)
A number of researchers have suggested that in order to understand the response properties of cells in the visual pathway, we must consider the statistical structure of the natural environment. In this paper, we focus on one aspect of that structure, namely, the correlational structure which is described by the amplitude or power spectra of natural scenes. We propose that the principle insight one gains from considering the image spectra is in understanding the relative sensitivity of cells tuned to different spatial frequencies. This study employs a model in which the peak sensitivity is constant as a function of frequency with linear bandwith increasing (i.e., approximately constant in octaves). In such a model, the "response magnitude " (i.e., vector length) of cells increases as a function of their optimal (or central) spatial frequency out to about 20 cyc/deg. The result is a code in which the response to natural scenes, whose amplitude spectra typically fall as 1/f, is roughly constant out to 20 cyc/deg. An important consideration in evaluating this model of sensitivity is the fact that natural scenes show considerable variability in their amplitude spectra, with individual scenes showing falloffs which are often steeper or shallower than 1/f. Using a new measure of image structure (the "rectified contrast spectrum " or "RCS") on a set of calibrated natural images, it is shown that a large part of the variability in the spectra is due to differences in the sparseness of local