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Article
Analysis of aerosol images using the scale-space primal sketch
We outline a method to analyze aerosol images using the scale-space representation. The pictures, which are photographs of an aerosol generated by a fuel injector, contain phenomena that by a human observer ar...
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Article
Scale-space behaviour of local extrema and blobs
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 treat...
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Article
Discrete derivative approximations with scale-space properties: A basis for low-level feature extraction
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...
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Article
Detecting salient blob-like image structures and their scales with a scale-space primal sketch: A method for focus-of-attention
This article presents: (i) a multiscale representation of grey-level shape called the scale-space primal sketch, which makes explicit both features in scale-space and the relations between structures at differ...
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Article
Direct computation of shape cues using scale-adapted spatial derivative operators
This paper addresses the problem of computing cues to the three-dimensional structure of surfaces in the world directly from the local structure of the brightness pattern of either a single monocular image or ...
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Article
Feature Detection with Automatic Scale Selection
The fact that objects in the world appear in different ways depending on the scale of observation has important implications if one aims at describing them. It shows that the notion of scale is of utmost impor...
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Article
Edge Detection and Ridge Detection with Automatic Scale Selection
When computing descriptors of image data, the type of information that can be extracted may be strongly dependent on the scales at which the image operators are applied. This article presents a systematic meth...
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Article
An automatic assessment scheme for steel quality inspection
This paper presents an automatic system for steel quality assessment, by measuring textural properties of carbide distributions. In current steel inspection, specially etched and polished steel specimen surfa...
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Article
A Distance Measure and a Feature Likelihood Map Concept for Scale-Invariant Model Matching
This paper presents two approaches for evaluating multi-scale feature-based object models. Within the first approach, a scale-invariant distance measure is proposed for comparing two image representations in t...
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Article
Generalized Gaussian Scale-Space Axiomatics Comprising Linear Scale-Space, Affine Scale-Space and Spatio-Temporal Scale-Space
This paper describes a generalized axiomatic scale-space theory that makes it possible to derive the notions of linear scale-space, affine Gaussian scale-space and linear spatio-temporal scale-space using a si...
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Article
Open AccessScale Selection Properties of Generalized Scale-Space Interest Point Detectors
Scale-invariant interest points have found several highly successful applications in computer vision, in particular for image-based matching and recognition.
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Article
Open AccessImage Matching Using Generalized Scale-Space Interest Points
The performance of matching and object recognition methods based on interest points depends on both the properties of the underlying interest points and the choice of associated image descriptors. This paper d...
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Article
Open AccessTime-Causal and Time-Recursive Spatio-Temporal Receptive Fields
We present an improved model and theory for time-causal and time-recursive spatio-temporal receptive fields, obtained by a combination of Gaussian receptive fields over the spatial domain and first-order integ...
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Article
Open AccessTemporal Scale Selection in Time-Causal Scale Space
When designing and develo** scale selection mechanisms for generating hypotheses about characteristic scales in signals, it is essential that the selected scale levels reflect the extent of the underlying st...
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Article
Open AccessSpatio-Temporal Scale Selection in Video Data
This work presents a theory and methodology for simultaneous detection of local spatial and temporal scales in video data. The underlying idea is that if we process video data by spatio-temporal receptive fiel...
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Article
Open AccessDynamic Texture Recognition Using Time-Causal and Time-Recursive Spatio-Temporal Receptive Fields
This work presents a first evaluation of using spatio-temporal receptive fields from a recently proposed time-causal spatio-temporal scale-space framework as primitives for video analysis. We propose a new fam...
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Article
Open AccessProvably Scale-Covariant Continuous Hierarchical Networks Based on Scale-Normalized Differential Expressions Coupled in Cascade
This article presents a theory for constructing hierarchical networks in such a way that the networks are guaranteed to be provably scale covariant. We first present a general sufficiency argument for obtainin...
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Article
Open AccessScale-Covariant and Scale-Invariant Gaussian Derivative Networks
This paper presents a hybrid approach between scale-space theory and deep learning, where a deep learning architecture is constructed by coupling parameterized scale-space operations in cascade. By sharing the...
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Article
Open AccessScale-Invariant Scale-Channel Networks: Deep Networks That Generalise to Previously Unseen Scales
The ability to handle large scale variations is crucial for many real-world visual tasks. A straightforward approach for handling scale in a deep network is to process an image at several scales simultaneously...
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Article
Open AccessDiscrete Approximations of Gaussian Smoothing and Gaussian Derivatives
This paper develops an in-depth treatment concerning the problem of approximating the Gaussian smoothing and the Gaussian derivative computations in scale-space theory for application on discrete data. With cl...