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2019
We introduce a novel scale-space concept that is inspired by inpainting-based lossy image compression and the recent denoising by inpainting method of Adam et al. (2017). In the discrete setting, the main idea behind these so-called sparsification scale-spaces is as follows: Starting with the original image, one subsequently removes a pixel until a ...
Cárdenas, Marcelo +2 more
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We introduce a novel scale-space concept that is inspired by inpainting-based lossy image compression and the recent denoising by inpainting method of Adam et al. (2017). In the discrete setting, the main idea behind these so-called sparsification scale-spaces is as follows: Starting with the original image, one subsequently removes a pixel until a ...
Cárdenas, Marcelo +2 more
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IEEE Winter Conference on Applications of Computer Vision, 2014
The state-of-the-art SIFT flow has been widely adopted for the general image matching task, especially in dealing with image pairs from similar scenes but with different object configurations. However, the way in which the dense SIFT features are computed at a fixed scale in the SIFT flow method limits its capability of dealing with scenes of large ...
Weichao Qiu +4 more
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The state-of-the-art SIFT flow has been widely adopted for the general image matching task, especially in dealing with image pairs from similar scenes but with different object configurations. However, the way in which the dense SIFT features are computed at a fixed scale in the SIFT flow method limits its capability of dealing with scenes of large ...
Weichao Qiu +4 more
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Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1993
Currently the aspect graph is computed under the assumption of perfect resolution in the viewpoint, the projected image, and the object shape. Visual detail is represented that an observer might never see in practice. By introducing scale into this framework, a mechanism is provided for selecting levels of detail that are large enough to merit explicit
David W. Eggert +4 more
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Currently the aspect graph is computed under the assumption of perfect resolution in the viewpoint, the projected image, and the object shape. Visual detail is represented that an observer might never see in practice. By introducing scale into this framework, a mechanism is provided for selecting levels of detail that are large enough to merit explicit
David W. Eggert +4 more
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Image and Vision Computing, 1997
It is argued that image measurements should satisfy two requirements of physical plausibility: the measurements are of non-zero scale and non-zero imprecision; and two required invariances, nothing is lost by expanding the image and nothing is lost by increasing the contrast of the image.
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It is argued that image measurements should satisfy two requirements of physical plausibility: the measurements are of non-zero scale and non-zero imprecision; and two required invariances, nothing is lost by expanding the image and nothing is lost by increasing the contrast of the image.
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The Scales of Innovation Spaces
2008This compact and authoritative book brings together the topical themes of networks and governance to advance understanding of the determinants of local economic development in the context of increasingly global relationships.
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Fourth IEEE International Conference on Computer Vision Systems (ICVS'06), 2006
Over the last 30 years, scale space representations have emerged as a fundamental tool for allowing systems to become increasingly robust against changes in camera viewpoint. Unfortunately, the implementation details that are required to properly construct a scale space representation are not published in the literature.
Ross S. Eaton +4 more
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Over the last 30 years, scale space representations have emerged as a fundamental tool for allowing systems to become increasingly robust against changes in camera viewpoint. Unfortunately, the implementation details that are required to properly construct a scale space representation are not published in the literature.
Ross S. Eaton +4 more
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Statistical analysis of scale-space
Signal Processing, 1992zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Vijaykumar A. Topkar, Arun K. Sood
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1995
A segmentation scheme based on tracing objects and borders through scale space is proposed. Scale space allows to create a hierarchical representation of input data which can be used to tessellate input space into objects with closed and orientable borders. For analyzing the structure of scale space, a neural network approach using synchronizing neural
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A segmentation scheme based on tracing objects and borders through scale space is proposed. Scale space allows to create a hierarchical representation of input data which can be used to tessellate input space into objects with closed and orientable borders. For analyzing the structure of scale space, a neural network approach using synchronizing neural
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Scale-Spaces, PDE’s, and Scale-Invariance
2001In the literature an image scale-space is usually defined as the solution of an initial value problem described by a PDE, such as a linear or nonlinear diffusion equation. Alternatively, scale-spaces can be defined in an axiomatic way starting from a fixed-scale image operator (e.g.
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Localization Scale Selection for Scale-Space Segmentation
2005In this work the relation between scale-space image segmentation and selection of the localization scale is examined first, and a scale selection approach is consequently proposed in the segmentation context. Considering the segmentation part, gradient watersheds are applied to the non-linear scale-space domain followed by a grouping operation.
Sokratis Makrogiannis +1 more
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