Results 1 - 10 of 5,388

The pyramid match kernel: Discriminative classification with sets of image features

by Kristen Grauman, Trevor Darrell - IN ICCV , 2005
"... Discriminative learning is challenging when examples are sets of features, and the sets vary in cardinality and lack any sort of meaningful ordering. Kernel-based classification methods can learn complex decision boundaries, but a kernel over unordered set inputs must somehow solve for correspondenc ..."
Abstract - Cited by 544 (29 self) - Add to MetaCart
for correspondences – generally a computationally expensive task that becomes impractical for large set sizes. We present a new fast kernel function which maps unordered feature sets to multi-resolution histograms and computes a weighted histogram intersection in this space. This “pyramid match” computation is linear

Similarity of Color Images

by Markus Stricker, Markus Orengo , 1995
"... We describe two new color indexing techniques. The first one is a more robust version of the commonly used color histogram indexing. In the index we store the cumulative color histograms. The L 1 -, L 2 -, or L1 -distance between two cumulative color histograms can be used to define a similarity mea ..."
Abstract - Cited by 495 (2 self) - Add to MetaCart
We describe two new color indexing techniques. The first one is a more robust version of the commonly used color histogram indexing. In the index we store the cumulative color histograms. The L 1 -, L 2 -, or L1 -distance between two cumulative color histograms can be used to define a similarity

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
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

Matching words and pictures

by Kobus Barnard, Pinar Duygulu, David Forsyth, Nando De Freitas, David M. Blei, Michael I. Jordan - JOURNAL OF MACHINE LEARNING RESEARCH , 2003
"... We present a new approach for modeling multi-modal data sets, focusing on the specific case of segmented images with associated text. Learning the joint distribution of image regions and words has many applications. We consider in detail predicting words associated with whole images (auto-annotation ..."
Abstract - Cited by 665 (40 self) - Add to MetaCart
We present a new approach for modeling multi-modal data sets, focusing on the specific case of segmented images with associated text. Learning the joint distribution of image regions and words has many applications. We consider in detail predicting words associated with whole images (auto

Shiftable Multi-scale Transforms

by Eero Simoncelli, William T. Freeman, Edward H. Adelson, David J. Heeger , 1992
"... Orthogonal wavelet transforms have recently become a popular representation for multiscale signal and image analysis. One of the major drawbacks of these representations is their lack of translation invariance: the content of wavelet subbands is unstable under translations of the input signal. Wavel ..."
Abstract - Cited by 562 (36 self) - Add to MetaCart
. Wavelet transforms are also unstable with respect to dilations of the input signal, and in two dimensions, rotations of the input signal. We formalize these problems by defining a type of translation invariance that we call "shiftability". In the spatial domain, shiftability corresponds to a

Multiresolution grayscale and rotation invariant texture classification with local binary patterns

by Timo Ojala, Matti Pietikäinen, Topi Mäenpää - IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 2002
"... This paper presents a theoretically very simple, yet efficient, multiresolution approach to gray-scale and rotation invariant texture classification based on local binary patterns and nonparametric discrimination of sample and prototype distributions. The method is based on recognizing that certain ..."
Abstract - Cited by 1299 (39 self) - Add to MetaCart
that certain local binary patterns, termed "uniform," are fundamental properties of local image texture and their occurrence histogram is proven to be a very powerful texture feature. We derive a generalized gray-scale and rotation invariant operator presentation that allows for detecting the "

Real-Time Obstacle Avoidance for Manipulators and Mobile Robots

by Oussama Khatib - INT. JOUR OF ROBOTIC RESEARCH , 1986
"... This paper presents a unique real-time obstacle avoidance approach for manipulators and mobile robots based on the artificial potential field concept. Collision avoidance, tradi-tionally considered a high level planning problem, can be effectively distributed between different levels of control, al- ..."
Abstract - Cited by 1345 (28 self) - Add to MetaCart
control. We reformulated the manipulator con-trol problem as direct control of manipulator motion in oper-ational space—the space in which the task is originally described—rather than as control of the task’s corresponding joint space motion obtained only after geometric and kine

Recognition without Correspondence using Multidimensional Receptive Field Histograms

by Bernt Schiele, James L. Crowley - International Journal of Computer Vision , 2000
"... . The appearance of an object is composed of local structure. This local structure can be described and characterized by a vector of local features measured by local operators such as Gaussian derivatives or Gabor filters. This article presents a technique where appearances of objects are represente ..."
Abstract - Cited by 262 (20 self) - Add to MetaCart
are represented by the joint statistics of such local neighborhood operators. As such, this represents a new class of appearance based techniques for computer vision. Based on joint statistics, the paper develops techniques for the identification of multiple objects at arbitrary positions and orientations in a

A Parametric Texture Model based on Joint Statistics of Complex Wavelet Coefficients

by Javier Portilla, Eero P. Simoncelli - INTERNATIONAL JOURNAL OF COMPUTER VISION , 2000
"... We present a universal statistical model for texture images in the context of an overcomplete complex wavelet transform. The model is parameterized by a set of statistics computed on pairs of coefficients corresponding to basis functions at adjacent spatial locations, orientations, and scales. We de ..."
Abstract - Cited by 424 (13 self) - Add to MetaCart
We present a universal statistical model for texture images in the context of an overcomplete complex wavelet transform. The model is parameterized by a set of statistics computed on pairs of coefficients corresponding to basis functions at adjacent spatial locations, orientations, and scales. We

Gravity coupled with matter and the foundation of non commutative geometry

by Alain Connes , 1996
"... We first exhibit in the commutative case the simple algebraic relations between the algebra of functions on a manifold and its infinitesimal length element ds. Its unitary representations correspond to Riemannian metrics and Spin structure while ds is the Dirac propagator ds = ×— × = D −1 where D i ..."
Abstract - Cited by 343 (17 self) - Add to MetaCart
We first exhibit in the commutative case the simple algebraic relations between the algebra of functions on a manifold and its infinitesimal length element ds. Its unitary representations correspond to Riemannian metrics and Spin structure while ds is the Dirac propagator ds = ×— × = D −1 where D
Results 1 - 10 of 5,388