Results 1 - 10 of 68,257

Kernel-Based Object Tracking

by Dorin Comaniciu, Visvanathan Ramesh, Peter Meer , 2003
"... A new approach toward target representation and localization, the central component in visual tracking of non-rigid objects, is proposed. The feature histogram based target representations are regularized by spatial masking with an isotropic kernel. The masking induces spatially-smooth similarity fu ..."
Abstract - Cited by 900 (4 self) - Add to MetaCart
information, Kalman tracking using motion models, and face tracking. Keywords: non-rigid object tracking; target localization and representation; spatially-smooth similarity function; Bhattacharyya coefficient; face tracking. 1

Reconstruction and Representation of 3D Objects with Radial Basis Functions

by J. C. Carr, R. K. Beatson, J. B. Cherrie, T. J. Mitchell, W. R. Fright, B. C. McCallum, T. R. Evans - Computer Graphics (SIGGRAPH ’01 Conf. Proc.), pages 67–76. ACM SIGGRAPH , 2001
"... We use polyharmonic Radial Basis Functions (RBFs) to reconstruct smooth, manifold surfaces from point-cloud data and to repair incomplete meshes. An object's surface is defined implicitly as the zero set of an RBF fitted to the given surface data. Fast methods for fitting and evaluating RBFs al ..."
Abstract - Cited by 505 (1 self) - Add to MetaCart
We use polyharmonic Radial Basis Functions (RBFs) to reconstruct smooth, manifold surfaces from point-cloud data and to repair incomplete meshes. An object's surface is defined implicitly as the zero set of an RBF fitted to the given surface data. Fast methods for fitting and evaluating RBFs

Hierarchical Models of Object Recognition in Cortex

by Maximilian Riesenhuber, Tomaso Poggio , 1999
"... The classical model of visual processing in cortex is a hierarchy of increasingly sophisticated representations, extending in a natural way the model of simple to complex cells of Hubel and Wiesel. Somewhat surprisingly, little quantitative modeling has been done in the last 15 years to explore th ..."
Abstract - Cited by 836 (84 self) - Add to MetaCart
the biological feasibility of this class of models to explain higher level visual processing, such as object recognition. We describe a new hierarchical model that accounts well for this complex visual task, is consistent with several recent physiological experiments in inferotemporal cortex and makes testable

Object Detection with Discriminatively Trained Part Based Models

by Pedro F. Felzenszwalb, Ross B. Girshick, David McAllester, Deva Ramanan
"... We describe an object detection system based on mixtures of multiscale deformable part models. Our system is able to represent highly variable object classes and achieves state-of-the-art results in the PASCAL object detection challenges. While deformable part models have become quite popular, their ..."
Abstract - Cited by 1422 (49 self) - Add to MetaCart
and optimizing the latent SVM objective function.

Distortion invariant object recognition in the dynamic link architecture

by Martin Lades, Jan C. Vorbrüggen, Joachim Buhmann, Christoph v. d. Malsburg, Rolf P. Würtz, Wolfgang Konen - IEEE TRANSACTIONS ON COMPUTERS , 1993
"... We present an object recognition system based on the Dynamic Link Architecture, which is an extension to classical Artificial Neural Networks. The Dynamic Link Architecture ex-ploits correlations in the fine-scale temporal structure of cellular signals in order to group neurons dynamically into hig ..."
Abstract - Cited by 637 (80 self) - Add to MetaCart
matching cost function. Our implementation on a transputer network successfully achieves recognition of human faces and office objects from gray level camera images. The performance of the program is evaluated by a statistical analysis of recognition results from a portrait gallery comprising images of 87

Thresholding of statistical maps in functional neuroimaging using the false discovery rate.

by Christopher R Genovese , Nicole A Lazar , Thomas Nichols - NeuroImage , 2002
"... Finding objective and effective thresholds for voxelwise statistics derived from neuroimaging data has been a long-standing problem. With at least one test performed for every voxel in an image, some correction of the thresholds is needed to control the error rates, but standard procedures for mult ..."
Abstract - Cited by 521 (9 self) - Add to MetaCart
Finding objective and effective thresholds for voxelwise statistics derived from neuroimaging data has been a long-standing problem. With at least one test performed for every voxel in an image, some correction of the thresholds is needed to control the error rates, but standard procedures

The Lumigraph

by Steven J. Gortler, Radek Grzeszczuk, Richard Szeliski, Michael F. Cohen - IN PROCEEDINGS OF SIGGRAPH 96 , 1996
"... This paper discusses a new method for capturing the complete appearanceof both synthetic and real world objects and scenes, representing this information, and then using this representation to render images of the object from new camera positions. Unlike the shape capture process traditionally used ..."
Abstract - Cited by 1025 (39 self) - Add to MetaCart
This paper discusses a new method for capturing the complete appearanceof both synthetic and real world objects and scenes, representing this information, and then using this representation to render images of the object from new camera positions. Unlike the shape capture process traditionally used

SNOPT: An SQP Algorithm For Large-Scale Constrained Optimization

by Philip E. Gill, Walter Murray, Michael A. Saunders , 2002
"... Sequential quadratic programming (SQP) methods have proved highly effective for solving constrained optimization problems with smooth nonlinear functions in the objective and constraints. Here we consider problems with general inequality constraints (linear and nonlinear). We assume that first deriv ..."
Abstract - Cited by 597 (24 self) - Add to MetaCart
Sequential quadratic programming (SQP) methods have proved highly effective for solving constrained optimization problems with smooth nonlinear functions in the objective and constraints. Here we consider problems with general inequality constraints (linear and nonlinear). We assume that first

Fast and robust fixed-point algorithms for independent component analysis

by Aapo Hyvärinen - IEEE TRANS. NEURAL NETW , 1999
"... Independent component analysis (ICA) is a statistical method for transforming an observed multidimensional random vector into components that are statistically as independent from each other as possible. In this paper, we use a combination of two different approaches for linear ICA: Comon’s informat ..."
Abstract - Cited by 884 (34 self) - Add to MetaCart
information-theoretic approach and the projection pursuit approach. Using maximum entropy approximations of differential entropy, we introduce a family of new contrast (objective) functions for ICA. These contrast functions enable both the estimation of the whole decomposition by minimizing mutual information

The Coordination of Arm Movements: An Experimentally Confirmed Mathematical Model

by Tamar Flash, Neville Hogans - Journal of neuroscience , 1985
"... This paper presents studies of the coordination of volun-tary human arm movements. A mathematical model is for-mulated which is shown to predict both the qualitative fea-tures and the quantitative details observed experimentally in planar, multijoint arm movements. Coordination is modeled mathematic ..."
Abstract - Cited by 688 (18 self) - Add to MetaCart
mathematically by defining an objective function, a measure of performance for any possi-ble movement. The unique trajectory which yields the best performance is determined using dynamic optimization the-ory. In the work presented here, the objective function is the square of the magnitude of jerk (rate
Results 1 - 10 of 68,257