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Pfinder: Real-time tracking of the human body

by Christopher Richard Wren, Ali Azarbayejani, Trevor Darrell, Alex Paul Pentland - IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 1997
"... Pfinder is a real-time system for tracking people and interpreting their behavior. It runs at 10Hz on a standard SGI Indy computer, and has performed reliably on thousands of people in many different physical locations. The system uses a multiclass statistical model of color and shape to obtain a 2D ..."
Abstract - Cited by 1464 (48 self) - Add to MetaCart
Pfinder is a real-time system for tracking people and interpreting their behavior. It runs at 10Hz on a standard SGI Indy computer, and has performed reliably on thousands of people in many different physical locations. The system uses a multiclass statistical model of color and shape to obtain a 2

RTP: A Transport Protocol for Real-Time Applications

by H. Schulzrinne, S. Casner, et al. , 1999
"... ..."
Abstract - Cited by 2394 (136 self) - Add to MetaCart
Abstract not found

Real-time human pose recognition in parts from single depth images

by Jamie Shotton, Andrew Fitzgibbon, Mat Cook, Toby Sharp, Mark Finocchio, Richard Moore, Alex Kipman, Andrew Blake - In In CVPR, 2011. 3
"... We propose a new method to quickly and accurately predict 3D positions of body joints from a single depth image, using no temporal information. We take an object recognition approach, designing an intermediate body parts representation that maps the difficult pose estimation problem into a simpler p ..."
Abstract - Cited by 550 (19 self) - Add to MetaCart
local modes. The system runs at 200 frames per second on consumer hardware. Our evaluation shows high accuracy on both synthetic and real test sets, and investigates the effect of several training parameters. We achieve state of the art accuracy in our comparison with related work and demonstrate

OPTICS: Ordering Points To Identify the Clustering Structure

by Mihael Ankerst, Markus M. Breunig, Hans-peter Kriegel, Jörg Sander , 1999
"... Cluster analysis is a primary method for database mining. It is either used as a stand-alone tool to get insight into the distribution of a data set, e.g. to focus further analysis and data processing, or as a preprocessing step for other algorithms operating on the detected clusters. Almost all of ..."
Abstract - Cited by 511 (49 self) - Add to MetaCart
of the well-known clustering algorithms require input parameters which are hard to determine but have a significant influence on the clustering result. Furthermore, for many real-data sets there does not even exist a global parameter setting for which the result of the clustering algorithm describes

Precomputed Radiance Transfer for Real-Time Rendering in Dynamic, Low-Frequency Lighting Environments

by Peter-pike Sloan, Jan Kautz, John Snyder - ACM Transactions on Graphics , 2002
"... We present a new, real-time method for rendering diffuse and glossy objects in low-frequency lighting environments that captures soft shadows, interreflections, and caustics. As a preprocess, a novel global transport simulator creates functions over the object's surface representing transfer of ..."
Abstract - Cited by 472 (28 self) - Add to MetaCart
We present a new, real-time method for rendering diffuse and glossy objects in low-frequency lighting environments that captures soft shadows, interreflections, and caustics. As a preprocess, a novel global transport simulator creates functions over the object's surface representing transfer

Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering

by Mikhail Belkin, Partha Niyogi - Advances in Neural Information Processing Systems 14 , 2001
"... Drawing on the correspondence between the graph Laplacian, the Laplace-Beltrami operator on a manifold, and the connections to the heat equation, we propose a geometrically motivated algorithm for constructing a representation for data sampled from a low dimensional manifold embedded in a higher ..."
Abstract - Cited by 664 (8 self) - Add to MetaCart
higher dimensional space. The algorithm provides a computationally efficient approach to nonlinear dimensionality reduction that has locality preserving properties and a natural connection to clustering. Several applications are considered.

Fast Algorithms for Mining Association Rules

by Rakesh Agrawal, Ramakrishnan Srikant , 1994
"... We consider the problem of discovering association rules between items in a large database of sales transactions. We present two new algorithms for solving this problem that are fundamentally different from the known algorithms. Empirical evaluation shows that these algorithms outperform the known a ..."
Abstract - Cited by 3551 (15 self) - Add to MetaCart
We consider the problem of discovering association rules between items in a large database of sales transactions. We present two new algorithms for solving this problem that are fundamentally different from the known algorithms. Empirical evaluation shows that these algorithms outperform the known

VLFeat -- An open and portable library of computer vision algorithms

by Andrea Vedaldi, et al. , 2010
"... ..."
Abstract - Cited by 514 (10 self) - Add to MetaCart
Abstract not found

GPFS: A Shared-Disk File System for Large Computing Clusters

by Frank Schmuck, Roger Haskin - In Proceedings of the 2002 Conference on File and Storage Technologies (FAST , 2002
"... GPFS is IBM's parallel, shared-disk file system for cluster computers, available on the RS/6000 SP parallel supercomputer and on Linux clusters. GPFS is used on many of the largest supercomputers in the world. GPFS was built on many of the ideas that were developed in the academic community ove ..."
Abstract - Cited by 518 (3 self) - Add to MetaCart
GPFS is IBM's parallel, shared-disk file system for cluster computers, available on the RS/6000 SP parallel supercomputer and on Linux clusters. GPFS is used on many of the largest supercomputers in the world. GPFS was built on many of the ideas that were developed in the academic community

The Macroscopic Behavior of the TCP Congestion Avoidance Algorithm

by Matthew Mathis, Jeffrey Semke, Jamshid Mahdavi, Teunis Ott , 1997
"... In this paper, we analyze a performance model for the TCP Congestion Avoidance algorithm. The model predicts the bandwidth of a sustained TCP connection subjected to light to moderate packet losses, such as loss caused by network congestion. It assumes that TCP avoids retransmission timeouts and alw ..."
Abstract - Cited by 648 (18 self) - Add to MetaCart
In this paper, we analyze a performance model for the TCP Congestion Avoidance algorithm. The model predicts the bandwidth of a sustained TCP connection subjected to light to moderate packet losses, such as loss caused by network congestion. It assumes that TCP avoids retransmission timeouts
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