Results 1 - 10 of 4,482

The "Independent Components" of Natural Scenes are Edge Filters

by Anthony J. Bell, Terrence J. Sejnowski , 1997
"... It has previously been suggested that neurons with line and edge selectivities found in primary visual cortex of cats and monkeys form a sparse, distributed representation of natural scenes, and it has been reasoned that such responses should emerge from an unsupervised learning algorithm that attem ..."
Abstract - Cited by 617 (29 self) - Add to MetaCart
It has previously been suggested that neurons with line and edge selectivities found in primary visual cortex of cats and monkeys form a sparse, distributed representation of natural scenes, and it has been reasoned that such responses should emerge from an unsupervised learning algorithm

A bayesian hierarchical model for learning natural scene categories

by Li Fei-fei - In CVPR , 2005
"... We propose a novel approach to learn and recognize natural scene categories. Unlike previous work [9, 17], it does not require experts to annotate the training set. We represent the image of a scene by a collection of local regions, denoted as codewords obtained by unsupervised learning. Each region ..."
Abstract - Cited by 948 (15 self) - Add to MetaCart
We propose a novel approach to learn and recognize natural scene categories. Unlike previous work [9, 17], it does not require experts to annotate the training set. We represent the image of a scene by a collection of local regions, denoted as codewords obtained by unsupervised learning. Each

Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories

by Cordelia Schmid - In CVPR
"... This paper presents a method for recognizing scene categories based on approximate global geometric correspondence. This technique works by partitioning the image into increasingly fine sub-regions and computing histograms of local features found inside each sub-region. The resulting “spatial pyrami ..."
Abstract - Cited by 1923 (47 self) - Add to MetaCart
and achieves high accuracy on a large database of fifteen natural scene categories. The spatial pyramid framework also offers insights into the success of several recently proposed image descriptions, including Torralba’s “gist ” and Lowe’s SIFT descriptors. 1.

NATURAL SCENES

by Patricia J. Bishop, Vice Provost, Dean Of Graduate Studies, Siddharth Rajkumar Borikar
"... The committee, the college and the University of Central Florida are not liable for any use of the materials presented in this study. FAST ALGORITHMS FOR FRAGMENT BASED COMPLETION IN IMAGES OF ..."
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The committee, the college and the University of Central Florida are not liable for any use of the materials presented in this study. FAST ALGORITHMS FOR FRAGMENT BASED COMPLETION IN IMAGES OF

Chromatic structure of natural scenes

by Thomas Wachtler, Te-won Lee, Terrence J. Sejnowski , 2001
"... We applied independent component analysis (ICA) to hyperspectral images in order to learn an efficient representation of color in natural scenes. In the spectra of single pixels, the algorithm found basis functions that had broadband spectra and basis functions that were similar to natural reflectan ..."
Abstract - Cited by 50 (5 self) - Add to MetaCart
We applied independent component analysis (ICA) to hyperspectral images in order to learn an efficient representation of color in natural scenes. In the spectra of single pixels, the algorithm found basis functions that had broadband spectra and basis functions that were similar to natural

Natural Scene Statistics At the Centre of Gaze

by Pamela Reinagel, Anthony M Zador - Network: Computation in Neural Systems , 1999
"... . Early stages of visual processing may exploit the characteristic structure of natural visual stimuli. This structure may differ from the intrinsic structure of natural scenes, because sampling of the environment is an active process. For example, humans move their eyes several times a second when ..."
Abstract - Cited by 97 (0 self) - Add to MetaCart
. Early stages of visual processing may exploit the characteristic structure of natural visual stimuli. This structure may differ from the intrinsic structure of natural scenes, because sampling of the environment is an active process. For example, humans move their eyes several times a second when

Detecting and reading text in natural scenes

by Xiangrong Chen, Alan L. Yuille - In Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition , 2004
"... This paper gives an algorithm for detecting and reading text in natural images. The algorithm is intended for use by blind and visually impaired subjects walking through city scenes. We first obtain a dataset of city images taken by blind and normally sighted subjects. From this dataset, we manually ..."
Abstract - Cited by 152 (2 self) - Add to MetaCart
This paper gives an algorithm for detecting and reading text in natural images. The algorithm is intended for use by blind and visually impaired subjects walking through city scenes. We first obtain a dataset of city images taken by blind and normally sighted subjects. From this dataset, we

Multiple-Instance Learning for Natural Scene Classification

by Oded Maron, Aparna Lakshmi Ratan - In The Fifteenth International Conference on Machine Learning , 1998
"... Multiple-Instance learning is a way of modeling ambiguity in supervised learning examples. Each example is a bag of instances, but only the bag is labeled - not the individual instances. A bag is labeled negative if all the instances are negative, and positive if at least one of the instances in pos ..."
Abstract - Cited by 229 (2 self) - Add to MetaCart
in positive. We apply the Multiple-Instance learning framework to the problem of learning how to classify natural images. Images are inherently ambiguous since they can represent many different things. A user labels an image as positive if the image somehow contains the concept. Each image is a bag

Frequency of metamerism in natural scenes

by David H. Foster, Kinjiro Amano, Sérgio M. C. Nascimento, Michael J. Foster - Journal of the Optical Society of America A , 2006
"... America A and is made available as an electronic reprint with the permission of OSA. The paper can also be found at the following URL on the OSA website: ..."
Abstract - Cited by 48 (17 self) - Add to MetaCart
America A and is made available as an electronic reprint with the permission of OSA. The paper can also be found at the following URL on the OSA website:

Disparity statistics in natural scenes

by Yang Liu, Alan C. Bovik, Lawrence K. Cormack
"... Binocular disparity is the input to stereopsis, which is a very strong depth cue in humans. However, the distribution of binocular disparities in natural environments has not been quantitatively measured. In this study, we converted distances from accurate range maps of forest scenes and indoor scen ..."
Abstract - Cited by 9 (4 self) - Add to MetaCart
Binocular disparity is the input to stereopsis, which is a very strong depth cue in humans. However, the distribution of binocular disparities in natural environments has not been quantitatively measured. In this study, we converted distances from accurate range maps of forest scenes and indoor
Results 1 - 10 of 4,482