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Discrete derivative approximations with scale-space properties. A basis for low-level feature extraction

Journal of Mathematical Imaging and vision 1993年第4期3卷 349-349页

作者： Lindeberg, Tony Department of Numerical Analysis and Computing Science Royal Institute of Technology Computational Vision and Active Perception Laboratory Stockholm Sweden

This article shows how discrete derivative approximations can be defined so thatscale-space properties hold exactly also in the discrete domain. Starting from a set of natural requirements on the first processing stages of a visual system,the visual front end, it gives an axiomatic derivation of how a multiscale representation of derivative approximations can be constructed from a discrete signal, so that it possesses analgebraic structure similar to that possessed by the derivatives of the traditional scale-space representation in the continuous domain. A family of kernels is derived that constitutediscrete analogues to the continuous Gaussian derivatives. The representation has theoretical advantages over other discretizations of the scale-space theory in the sense that operators that commute before discretizationcommute after discretization. Some computational implications of this are that derivative approximations can be computeddirectly from smoothed data and that this will giveexactly the same result as convolution with the corresponding derivative approximation kernel. Moreover, a number ofnormalization conditions are automatically satisfied. The proposed methodology leads to a scheme of computations of multiscale low-level feature extraction that is conceptually very simple and consists of four basic steps: (i)large support convolution smoothing, (ii)small support difference computations, (iii)point operations for computing differential geometric entities, and (iv)nearest-neighbour operations for feature detection. Applications demonstrate how the proposed scheme can be used for edge detection and junction detection based on derivatives up to order three.

关键词： computer vision digital signal processing discrete approximation edge detection Gaussian derivative Gaussian filtering junction detection multiscale representation scale-space smoothing visual front end

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ON SCALE AND RESOLUTION IN active analysis OF LOCAL IMAGE STRUCTURE

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IMAGE AND vision computing 1990年第4期8卷 289-296页

作者： BRUNNSTROM, K EKLUNDH, JO LINDEBERG, T Computational Vision and Active Perception Laboratory Department of Numerical Analysis and Computing Science Royal Institute of Technology S-100 44 Stockholm Sweden

Focus-of-attention is extremely important in human visual perception. If computer vision systems are to perform tasks in a complex, dynamic world they will have to be able to control processing in a way that is analogous to visual attention in humans. Problems connected to foveation (examination of selected regions of the world at high resolution) are examined. In particular, the problem of finding and classifying junctions from this aspect is considered. It is shown that foveation as simulated by controlled, active zooming in conjunction with scale-space techniques allows for robust detection and classification of junctions.

关键词： FOVEATION SCALE RESOLUTION JUNCTION CLASSIFICATION SCALE-SPACE TECHNIQUES FOCUS-OF-ATTENTION active vision HISTOGRAM analysis

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Scale-space behaviour of local extrema and blobs

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Journal of Mathematical Imaging and vision 1992年第1期1卷 65-65页

作者： Lindeberg, Tony Computational Vision and Active Perception Laboratory (CVAP) Department of Numerical Analysis and Computing Science Royal Institute of Technology Stockholm Sweden

Elementary techniques from real analysis, and singularity theory are applied to derive analytical results for the behaviour in scale-space of critical points and related entities. The main results of the treatment com... 详细信息

关键词： bifurcation blob blob event classification computer vision critical point digital signal processing drift velocity extremum region multi-scale representation scale-space singularity

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Dynamic fixation and active perception

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INTERNATIONAL JOURNAL OF computer vision 1996年第2期17卷 113-135页

作者： Pahlavan, K Uhlin, T Eklundh, JO Computational Vision and Active Perception Laboratory (CVAP) Department of Numerical Analysis and Computing Science Royal Institute of Technology S-100 44 Stockholm Sweden

Fixation is the link between the physical environment and the visual observer, both of which can be dynamic. That is, dynamic fixation serves the task of preserving a reference point in the world, despite relative motion. In this respect, fixation is dynamical in two senses: in response to voluntary changes of fixation point or attentive cues-gaze shiftings, and in response to the desire to compensate for the retinal slip-gaze holding. The work presented here, addresses the vergence movement and preservation of binocular fixation during smooth pursuit. This movement is a crucial component of fixation. The two vergence processes, disparity vergence and accommodative vergence, are described;a novel algorithm for robust disparity vergence and an active approach for blur detection and depth from defocus are presented. The main characteristics of the disparity vergence technique are the simplicity of the algorithm, the influence of both left and right images in the course of fixation and the agreement with the fixation model of primates. The major characteristic of the suggested algorithm for blur detection is its active approach which makes it suitable for achieving qualitative and reasonable depth estimations without unrealistic assumptions about the structures in the images. The paper also covers the integration of the two processes disparity vergence and accommodation vergence which are in turn accomplished by an integration of the disparity and blur stimuli. This integration is accounted for in both static and dynamic experiments.

关键词： computer vision

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Segmentation and classification of edges using minimum description length approximation and complementary junction cues

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computer vision AND IMAGE UNDERSTANDING 1997年第1期67卷 88-98页

作者： Lindeberg, T Li, MX Computational Vision and Active Perception Laboratory (CVAP) Department of Numerical Analysis and Computing Science Royal Institute of Technology S-100 44 Stockholm Sweden

This article presents a method for segmenting and classifying edges using minimum description length (MDL) approximation with automatically generated break points. A scheme is proposed where junction candidates are first detected in a multiscale preprocessing step, which generates junction candidates with associated regions of interest. These junction features are matched to edges based on spatial coincidence, For each matched pair, a tentative break point is introduced at the edge point closest to the junction. Finally, these feature combinations serve as input for an MDL approximation method which tests the validity of the break point hypotheses and classifies the resulting edge segments as either ''straight'' or ''curved.'' Experiments on real world image data demonstrate the viability of the approach. (C) 1997 Academic Press.

关键词： Edge detection

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Closing the loop: Detection and pursuit of a moving object by a moving observer

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IMAGE AND vision computing 1996年第4期14卷 265-275页

作者： Nordlund, P Uhlin, T Computational Vision and Active Perception Laboratory (CVAP) Department of Numerical Analysis and Computing Science Royal Institute of Technology S-100 44 Stockholm Sweden

We present an integrated system which is able to pursue a moving object and maintain the object centered in the image by controlling a robot-head. The system contains three parts: independent motion detection, tracking, and control of a robot-head. This paper focuses on the detection mechanism, and briefly discusses the tracking and control issues. The system runs continuously in time and updates the object localization at a frame-rate of 25 Hz. The moving object can be tracked, although the observer performs an unknown independent motion, involving both translation and rotation. We focus on a simple motion detection algorithm, since computational cost is of major importance for real-time systems with feedback. The algorithm is noniterative and computationally inexpensive. The running time complexity is O(n) for an image containing n pixels. The image-processing takes place on a MaxVideo200 pipeline processor, and the head control algorithm is running on a Transputer T800 network. Some offline experimental results are presented, where comparisons are made between affine and translational image motion models.

关键词： normal velocity real-time system tracking

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active fixation for scene exploration

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INTERNATIONAL JOURNAL OF computer vision 1996年第2期17卷 137-162页

作者： Brunnstrom, K Eklundh, JO Uhlin, T Computational Vision and Active Perception Laboratory (CVAP) Department of Numerical Analysis and Computing Science KTH (Royal Institute of Technology) S-100 44 Stockholm Sweden

It is well-known that active selection of fixation points in humans is highly context and task dependent. It is therefore likely that successful computational processes for fixation in active vision should be so too. We are considering active fixation in the context of recognition of man-made objects characterized by their shapes. In this situation the qualitative shape and type of observed junctions play an important role. The fixations are driven by a grouping strategy, which forms sets of connected junctions separated from the surrounding at depth discontinuities. We have furthermore developed a methodology for rapid active detection and classification of junctions by selection of fixation points. The approach is based on direct computations from image data and allows integration of stereo and accommodation cues with luminance information. This work form a part of an effort to perform active recognition of generic objects, in the spirit of Malik and Biederman, but on real imagery rather than on line-drawings.

关键词： active vision active detection Junction Device Component fixation image data Fixation Recognition (Psychology) Accommodation Line drawings Shape Ocular Accommodation

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Projectively invariant decomposition and recognition of planar shapes

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INTERNATIONAL JOURNAL OF computer vision 1996年第2期17卷 193-209页

作者： Carlsson, S Computational Vision and Active Perception Laboratory (CVAP) Department of Numerical Analysis and Computing Science KTH (Royal Institute of Technology) S-100 44 Stockholm Sweden

An algorithm is presented for computing a decomposition of planar shapes into convex subparts represented by ellipses, The method is invariant to projective transformations of the shape, and thus the conic primitives can be used for matching and definition of invariants in the same way as points and lines. The method works for arbitrary planar shapes admitting at least four distinct tangents and it is based on finding ellipses with four points of contact to the given shape. The cross ratio computed from the four points on the ellipse can then be used as a projectively invariant index. It is demonstrated that a given shape has a unique parameter-free decomposition into a finite set of ellipses with unit cross ratio. For a given shape, each pair of ellipses can be used to compute two independent projective invariants. The set of invariants computed for each ellipse pair can be used as indexes to a hash table from which model hypothesis can be generated Examples of shape decomposition and recognition are given for synthetic shapes and shapes extracted from grey level images of real objects using edge detection.

关键词： computer vision

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Machine vision research at CVAP: An introduction

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INTERNATIONAL JOURNAL OF computer vision 1996年第2期17卷 107-112页

作者： Eklundh, JO Computational Vision and Active Perception Laboratory (CVAP) Department of Numerical Analysis and Computing Science KTH (Royal Institute of Technology) S-100 44 Stockholm Sweden

This paper deals with the problems on the recovery and shape and motion. It also focuses on what is representing shape. In addition, it touches a briefly on the geometry for computer vision which concerns surface modeling. However, this paper goes beyond the need to model geometry and shape for computer vision, in that is also aims at developing mathematically well-founded computational environments for studying geometry by itself.

关键词： computer vision

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Shape-adapted smoothing in estimation of 3-D shape cues from affine deformations of local 2-D brightness structure

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IMAGE AND vision computing 1997年第6期15卷 415-434页

作者： Lindeberg, T Garding, J Computational Vision and Active Perception Laboratory (CVAP) Department of Numerical Analysis and Computing Science KTH (Royal Institute of Technology) S-100 44 Stockholm Sweden

This article describes a method for reducing the shape distortions due to scale space smoothing that arise in the computation of 3-D shape cues using operators (derivatives) defined from scale-space representation. More precisely, we are concerned with a general class of methods for deriving 3-D shape cues from a 2-D image data based on the estimation of locally linearized deformations of brightness patterns. This class constitutes a common framework for describing several problems in computer vision (such as shape-from-texture, shape-from disparity-gradients, and motion estimation) and for expressing different algorithms in terms of similar types of visual front-end-operations. It is explained how surface orientation estimates will be biased due to the use of rotationally symmetric smoothing in the image domain. These effects can be reduced by extending the linear scale-space concept into an affine Gaussian scale-space representation and by performing affine shape adaptation of the smoothing kernels. This improves the accuracy of the surface orientation estimates, since the image descriptors, on which the methods are based, will be relative invariant under affine transformations, and the error thus confined to the higher-order terms in the locally linearized perspective transformation. A straightforward algorithm is presented for performing shape adaptation in practice. Experiments on real and synthetic images with known orientation demonstrate that in the presence of moderately high noise levels the accuracy is improved by typically one order of magnitude.

关键词： shape estimation shape from texture disparity adaptation affine deformation optic flow

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