Results 1 - 10 of 160,677

Object Tracking: A Survey

by Alper Yilmaz, Omar Javed, Mubarak Shah , 2006
"... The goal of this article is to review the state-of-the-art tracking methods, classify them into different categories, and identify new trends. Object tracking, in general, is a challenging problem. Difficulties in tracking objects can arise due to abrupt object motion, changing appearance patterns o ..."
Abstract - Cited by 701 (7 self) - Add to MetaCart
The goal of this article is to review the state-of-the-art tracking methods, classify them into different categories, and identify new trends. Object tracking, in general, is a challenging problem. Difficulties in tracking objects can arise due to abrupt object motion, changing appearance patterns

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
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

Robust Real-time Object Detection

by Paul Viola, Michael Jones - International Journal of Computer Vision , 2001
"... This paper describes a visual object detection framework that is capable of processing images extremely rapidly while achieving high detection rates. There are three key contributions. The first is the introduction of a new image representation called the “Integral Image ” which allows the features ..."
Abstract - Cited by 1184 (4 self) - Add to MetaCart
This paper describes a visual object detection framework that is capable of processing images extremely rapidly while achieving high detection rates. There are three key contributions. The first is the introduction of a new image representation called the “Integral Image ” which allows the features

The PASCAL Visual Object Classes (VOC) Challenge

by M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, A. Zisserman - INTERNATIONAL JOURNAL OF COMPUTER VISION
"... ... and detection, providing the vision and machine learning communities with a standard dataset of images and annotation, and standard evaluation procedures. Organised annually from 2005 to present, the challenge and its associated dataset has become accepted as the benchmark for object detection. ..."
Abstract - Cited by 629 (20 self) - Add to MetaCart
. This paper describes the dataset and evaluation procedure. We review the state-of-the-art in evaluated methods for both classification and detection, analyse whether the methods are statistically different, what they are learning from the images (e.g. the object or its context), and what the methods find

Linearizability: a correctness condition for concurrent objects

by Maurice P. Herlihy, Jeannette M. Wing , 1990
"... A concurrent object is a data object shared by concurrent processes. Linearizability is a correctness condition for concurrent objects that exploits the semantics of abstract data types. It permits a high degree of concurrency, yet it permits programmers to specify and reason about concurrent object ..."
Abstract - Cited by 1178 (28 self) - Add to MetaCart
be given by pre- and post-conditions. This paper defines linearizability, compares it to other correctness conditions, presents and demonstrates a method for proving the correctness of implementations, and shows how to reason about concurrent objects, given they are linearizable.

Logical foundations of object-oriented and frame-based languages

by Michael Kifer, Georg Lausen, James Wu - JOURNAL OF THE ACM , 1995
"... We propose a novel formalism, called Frame Logic (abbr., F-logic), that accounts in a clean and declarative fashion for most of the structural aspects of object-oriented and frame-based languages. These features include object identity, complex objects, inheritance, polymorphic types, query methods, ..."
Abstract - Cited by 876 (65 self) - Add to MetaCart
We propose a novel formalism, called Frame Logic (abbr., F-logic), that accounts in a clean and declarative fashion for most of the structural aspects of object-oriented and frame-based languages. These features include object identity, complex objects, inheritance, polymorphic types, query methods

Object class recognition by unsupervised scale-invariant learning

by R. Fergus, P. Perona, A. Zisserman - In CVPR , 2003
"... We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constellations of parts. A probabilistic representation is used for all aspects of the object: shape, appearance, occlusion and ..."
Abstract - Cited by 1127 (50 self) - Add to MetaCart
We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constellations of parts. A probabilistic representation is used for all aspects of the object: shape, appearance, occlusion

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
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

Object Recognition from Local Scale-Invariant Features

by David G. Lowe
"... An object recognition system has been developed that uses a new class of local image features. The features are invariant to image scaling, translation, and rotation, and partially invariant to illumination changes and affine or 3D projection. These features share similar properties with neurons in ..."
Abstract - Cited by 2739 (13 self) - Add to MetaCart
in multiple orientation planes and at multiple scales. The keys are used as input to a nearest-neighbor indexing method that identifies candidate object matches. Final verification of each match is achieved by finding a low-residual least-squares solution for the unknown model parameters. Experimental results

Multidimensional Access Methods

by Volker Gaede, Oliver Günther , 1998
"... Search operations in databases require special support at the physical level. This is true for conventional databases as well as spatial databases, where typical search operations include the point query (find all objects that contain a given search point) and the region query (find all objects that ..."
Abstract - Cited by 686 (3 self) - Add to MetaCart
Search operations in databases require special support at the physical level. This is true for conventional databases as well as spatial databases, where typical search operations include the point query (find all objects that contain a given search point) and the region query (find all objects
Results 1 - 10 of 160,677