Results 1 - 10 of 278

Maintaining multi-modality through mixture tracking

by Jaco Vermaak, Arnaud Doucet - In ICCV , 2003
"... In recent years particle filters have become a tremendously popular tool to perform tracking for non-linear and/or non-Gaussian models. This is due to their simplicity, generality and success over a wide range of challenging applications. Particle filters, and Monte Carlo methods in general, are how ..."
Abstract - Cited by 135 (2 self) - Add to MetaCart
In recent years particle filters have become a tremendously popular tool to perform tracking for non-linear and/or non-Gaussian models. This is due to their simplicity, generality and success over a wide range of challenging applications. Particle filters, and Monte Carlo methods in general

Coil sensitivity encoding for fast MRI. In:

by Klaas P Pruessmann , Markus Weiger , Markus B Scheidegger , Peter Boesiger - Proceedings of the ISMRM 6th Annual Meeting, , 1998
"... New theoretical and practical concepts are presented for considerably enhancing the performance of magnetic resonance imaging (MRI) by means of arrays of multiple receiver coils. Sensitivity encoding (SENSE) is based on the fact that receiver sensitivity generally has an encoding effect complementa ..."
Abstract - Cited by 193 (3 self) - Add to MetaCart
maps with scaling clear of modulus object contrast but still modulated by the ''sum-of-squares'' of absolute sensitivities. More homogeneous scaling is achieved by dividing by a body coil image. The ''sum-of-squares'' denominator is applicable only if the object

Tracking Human Motion Using Multiple Cameras

by Q. Cai, J. K. Aggarwal - In Proc. of the 13th International Conference on Pattern Recognition , 1996
"... This paper presents a framework for tracking human motion in an indoor environment from sequences of monocular grayscale images obtained from multiple fixed cameras. Multivariate Gaussian models are applied to find the most likely matches of human subjects between consecutive frames taken by cameras ..."
Abstract - Cited by 66 (1 self) - Add to MetaCart
This paper presents a framework for tracking human motion in an indoor environment from sequences of monocular grayscale images obtained from multiple fixed cameras. Multivariate Gaussian models are applied to find the most likely matches of human subjects between consecutive frames taken

Tracking and segmenting people in varying lighting conditions using colour

by Yogesh Raja, Stephen J. Mckenna, Shaogang Gong - In AFG , 1998
"... Colour cues were used to obtain robust detection and tracking of people in relatively unconstrained dynamic scenes. Gaussian mixture models were used to estimate probability densities of colour for skin, clothing and background. These models were used to detect, track and segment people, faces and h ..."
Abstract - Cited by 105 (16 self) - Add to MetaCart
implemented on a 200MHz PC tracks multiple objects in real-time. 1

GAUSSIAN NETWORKS

by J. N. Laneman, V. Gupta Co-director
"... by Utsaw Kumar The presence of inexpensive and powerful sensing and communication devices has made it possible to deploy large scale distributed systems for a variety of applications. Interactions among different components of such a system include communication of information and controlling dynami ..."
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by Utsaw Kumar The presence of inexpensive and powerful sensing and communication devices has made it possible to deploy large scale distributed systems for a variety of applications. Interactions among different components of such a system include communication of information and controlling

Propagation of Pixel Hypotheses for Multiple Objects Tracking

by Haris Baltzakis, Antonis A. Argyros
"... Abstract. In this paper we propose a new approach for tracking multiple objects in image sequences. The proposed approach differs from existing ones in important aspects of the representation of the location and the shape of tracked objects and of the uncertainty associated with them. The location a ..."
Abstract - Cited by 4 (1 self) - Add to MetaCart
object and the uncertainty associated with its track. The proposed tracking approach has been developed to support face and hand tracking for human-robot interaction. Nevertheless, it is readily applicable to a much broader class of multiple objects tracking problems. 1

Vision-Based Motion Tracking of Rigid Objects Using Prediction of Uncertainties

by Akio Kosaka, Goichi Nakazawa - In T. Fukuda (Ed.): Proc. IEEE Int. Conf. on Robotics and Automation , 1995
"... A vision-based motion tracking method described in this paper estimates the 3D position and orientation of a moving object of known shape at an average speed of 2.5 seconds per image frame even in complex environments using a conventional computer power. Given a coarse estimate of the initial 3D obj ..."
Abstract - Cited by 12 (2 self) - Add to MetaCart
object pose, the method first generates an expectation view from which visible model features are automatically selected. The method then extracts potentially matched image features from image regions bounded by the propagation of object motion uncertainty. The special aspect of our vision-based tracking

Specified Object Tracking Problem in an Environment of Multiple Moving

by unknown authors
"... Video based object tracking normally deals with non-stationary image streams that change over time. Robust and real time moving object tracking is considered to be a problematic issue in computer vision. Multiple object tracking has many practical applications in scene analysis for automated surveil ..."
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Video based object tracking normally deals with non-stationary image streams that change over time. Robust and real time moving object tracking is considered to be a problematic issue in computer vision. Multiple object tracking has many practical applications in scene analysis for automated

Probabilistic Deformable Surface Tracking From Multiple Videos

by Cedric Cagniart, Edmond Boyer, Slobodan Ilic, Technische Universität München
"... Abstract. In this paper, we address the problem of tracking the temporal evolution of arbitrary shapes observed in multi-camera setups. This is motivated by the ever growing number of applications that require consistent shape information along temporal sequences. The approach we propose considers a ..."
Abstract - Cited by 42 (13 self) - Add to MetaCart
for the uncertainty in the data acquisition process, this framework effectively handles missing data, relatively large reconstruction artefacts and multiple objects. Extensive experiments demonstrate the effectiveness and robustness of the method on various 4D datasets. 1

Propagation of Uncertainty in Bayesian Kernel Models - Application to Multiple-Step Ahead Forecasting

by Joaquin Quiñonero Candela, Joaquin Qui Nonero Candela, Jan Larsen, Agathe Girard, Carl Edward Rasmussen, Math Modelling
"... The object of Bayesian modelling is the predictive distribution, which in a forecasting scenario enables evaluation of forecasted values and their uncertainties. In this paper we focus on reliably estimating the predictive mean and variance of forecasted values using Bayesian kernel based models suc ..."
Abstract - Cited by 5 (1 self) - Add to MetaCart
The object of Bayesian modelling is the predictive distribution, which in a forecasting scenario enables evaluation of forecasted values and their uncertainties. In this paper we focus on reliably estimating the predictive mean and variance of forecasted values using Bayesian kernel based models
Results 1 - 10 of 278