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Segmentation-based object categorization

Known as: Segmentation based object categorization 
The image segmentation problem is concerned with partitioning an image into multiple regions according to some homogeneity criterion. This article is… Expand
Wikipedia

Related topics

Related topics

10 relations
Bag-of-words model in computer visionLOBPCGLanczos algorithmMatrix-free methods
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Broader (1)

Image segmentation

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2015
Highly Cited
2015
Training Deep Networks with Structured Layers by Matrix Backpropagation
Deep neural network architectures have recently produced excellent results in a variety of areas in artificial intelligence and… Expand
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Highly Cited
2014
Highly Cited
2014
Multiscale Combinatorial Grouping
We propose a unified approach for bottom-up hierarchical image segmentation and object candidate generation for recognition… Expand
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Highly Cited
2013
Highly Cited
2013
Robust Matrix Factorization with Unknown Noise
Many problems in computer vision can be posed as recovering a low-dimensional subspace from high-dimensional visual data… Expand
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Highly Cited
2009
Highly Cited
2009
Efficient, high-quality image contour detection
Image contour detection is fundamental to many image analysis applications, including image segmentation, object recognition and… Expand
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Highly Cited
2007
Highly Cited
2007
A Lagrangian Particle Dynamics Approach for Crowd Flow Segmentation and Stability Analysis
  • Saad Ali, M. Shah
  • IEEE Conference on Computer Vision and Pattern…
  • 2007
    • Corpus ID: 8190391
This paper proposes a framework in which Lagrangian particle dynamics is used for the segmentation of high density crowd flows… Expand
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Highly Cited
2005
Highly Cited
2005
A Vision Algorithm for Dynamic Detection of Moving Vehicles with a UAV
This paper presents a vision system for road traffic surveillance from sequences acquired from an unmanned aerial vehicle (UAV… Expand
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Highly Cited
2004
Highly Cited
2004
Contour and Texture Analysis for Image Segmentation
This paper provides an algorithm for partitioning grayscale images into disjoint regions of coherent brightness and texture… Expand
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Highly Cited
2004
Highly Cited
2004
Kernel k-means: spectral clustering and normalized cuts
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space… Expand
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Highly Cited
2004
Highly Cited
2004
A Unified View of Kernel k-means , Spectral Clustering and Graph Cuts
Recently, a variety of clustering algorithms have been proposed to handle data that is not linearly separable. Spectral… Expand
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Highly Cited
1998
Highly Cited
1998
Motion segmentation and tracking using normalized cuts
We propose a motion segmentation algorithm that aims to break a scene into its most prominent moving groups. A weighted graph is… Expand
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