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P-Net: A Representation for Partially-Sequenced, Multi-stream Activity

P-Net: A Representation for Partially-Sequenced, Multi-strea...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Yifan Shi Aaron F. Bobick GVU Center / College of Computing Georgia Tech Atlanta GA USA

In this paper, we devise a Propagation Net (P-Net) as a new mechanism for the representation and recognition of multi-stream activity. Most of daily activities can be represented by temporally partial ordered intervals where each interval has not only temporal constraint, i.e., before/after/duration, but also a logical relationship such as a and b both must happen. P-Net associates a node for each interval that is probabilistically triggered function dependent upon the state of its parent nodes. Each node is also associated with an observation distribution function that associates perceptual evidence. This evidence, generated by lower level vision modules, is a positive indicator of the elemental action. Using this architecture, we devise an iterative temporal sequencing algorithm that interprets a multi-dimensional observation sequence of visual evidence as a multi-stream propagation through the P-Net. Simple vision and motion-capture data experiments demonstrate the capabilities of our algorithm.

关键词： Hidden Markov models Books Detectors Pediatrics conferences Noise measurement computer vision

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The Beauvais Cathedral Project

The Beauvais Cathedral Project

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Peter K. Allen Alejandro Troccoli Benjamin Smith Ioannis Stamos Stephen Murray Department of Computer Science Columbia University New York NY USA Department of Computer Science CUNY USA Department of Art History and Archaeology Columbia University New York NY USA

Preserving cultural heritage and historic sites is an important problem. These sites are subject to erosion, vandalism, and as long-lived artifacts, they have gone through many phases of construction, damage and repair. It is important to keep an accurate record of these sites using 3-D model building technology as they currently are, so preservationists can track changes, foresee structural problems, and allow a wider audience to "virtually" see and tour these sites. Due to the complexity of these sites, building 3-D models is time consuming and difficult, usually involving much manual effort. This paper discusses new methods that can reduce the time to build a model using automatic methods. Examples of these methods are shown in reconstructing a model of the Cathedral of Saint-Pierre in Beauvais, France.

关键词： Three dimensional displays Buildings computer vision Solid modeling Meteorology pattern recognition conferences

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Omnidirectional Distributed vision System for a Team of Heterogeneous Robots

Omnidirectional Distributed Vision System for a Team of Hete...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Emanuele Menegatti Alberto Scarpa Dario Massarin Enrico Ros Enrico Pagello Intelligent Autonomous Systems Laboratory Department of Information Engineering University of Padua Italy Intelligent Autonomous Systems Laboratory Department of Information Engineering University of Padua

This paper presents a system designed to cooperatively track and share the information about moving objects using a multi-robot team. Every robot of the team is fitted with a different omnidirectional vision system running at different frame rates. The information gathered from every robot is broadcast to all the other robots and every robot fuses its own measurements with the information received from the teammates, building its own "vision of the world". The cooperation of the vision sensors enhances the capabilities of the single vision sensor. This work was implemented in the RoboCup domain, using our team of heterogeneous robot, but the approach is very general and can be used in any application where a team of robot has to track multiple objects. The system is designed to work with heterogeneous vision systems both in the camera design and in computational resources. Experiments in real game scenarios are presented.

关键词： Robots Robot sensing systems Time measurement Sensors Machine vision Tracking Position measurement

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Template-based recognition of Static Sitting Postures

Template-based Recognition of Static Sitting Postures

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Manli Zhu Aleix M. Martinez Hong Z. Tan Department of Electrical Engineering Ohio State Uinversity USA School of Electrical and Computer Engineering Purdue University USA

In this paper we introduce a generalization of Fisher-Rao's discriminant analysis and its application in a human-computer interaction scenario: a sensing chair. Our algorithm shows to be able to successfully estimate the underlying distributions of the pressure maps data of the sensing chair. Other linear discriminant techniques, such as LDA, had been found to be inadequate for the job; typically yielding inferior results than PCA. We compare our approach to several template-based approaches and show that the new discriminant function is comparable to the best approach classifier. This is important because generally each application tends to prefer a different algorithm. Fortunately, our new algorithm is usually the top one (or comparable to the top one). In this paper we will however restrict our study tothe classification of sitting postures.

关键词： Classification algorithms Sensors pattern recognition Algorithm design and analysis Principal component analysis conferences Leg

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Virtual Scene Control Using Human Body Postures

Virtual Scene Control Using Human Body Postures

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Satoshi Yonemoto Rin-ichiro Taniguchi Department of Intelligent Systems Kyushu University Fukuoka Japan Department of Intelligent Informatics Kyushu Sangyo University Fukuoka Japan

This paper describes a vision based 3D real-virtual interaction which enables realistic avatar motion control, and in which the virtual camera is controlled by the body posture of the user. The human motion analysis method is implemented by blob tracking. A physically-constrained motion synthesis method is implemented to generate realistic motion from a limit number of blobs. We address our framework to utilize virtual scene contexts as a priori knowledge. In order to make the virtual scene more realistically beyond the limitation of the real world sensing, we use a framework to augment the reality in the virtual scene by simulating various events of the real world. Concretely, we suppose that a virtual environment can provide action information for the avatar. 3rd-person viewpoint control coupled with body postures is also realized to directly access virtual objects.

关键词： Avatars Cameras Joints Humans Three dimensional displays conferences pattern recognition

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Generic Event Detection in Sports Video using Cinematic Features

Generic Event Detection in Sports Video using Cinematic Feat...

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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Ahmet Ekin A. Murat Tekalp Department of Electrical and Computer Engineering University of Rochester Rochester NY USA College of Engineering Koc University Istanbul Turkey

This paper presents real-time, or near real-time, probabilistic event detection methods for broadcast sports video using cinematic features, such as shot classes and slow-motion replays. Novel algorithms have been developed for probabilistic detection of soccer goal events and basketball play-break events in a generic framework. The proposed framework includes generic algorithms for automatic dominant (field) color region detection and shot boundary detection, and domain-specific shot classification algorithms for soccer and basketball. Finally, the detected goal events in soccer and play events in basketball are employed to generate summaries of long games. The efficiency and effectiveness of the proposed system and the algorithms have been shown over more than 13 hours of sports video captured by the broadcasters from different regions around the world.

关键词： Pixel Color Classification algorithms Feature extraction Histograms Event detection Games

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Principal Video Shot: Linking Low-Level Perceptional Features to Semantic Video Events

Principal Video Shot: Linking Low-Level Perceptional Feature...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Jianping Fan Hangzai Luo Department of Computer Science North Carolina State University Charlotte NC USA

In this paper, we propose a novel framework for semantic medical event characterization and detection by using principal video shots and semantic principal video shot classification. Specifically, the framework includes: (a) A semantic medical event characterization technique by using principal video shots in a specific surgery education video domain. (b) An automatic principal video shot detection algorithm by determining the domain-dependent and event-driven salient objects. (c) A semantic medical event detection technique by using Bayesian classifier, where the classifier parameters and structure are determined automatically by an adaptive Expectation-Maximization (EM) algorithm. For semantic medical event detection in a specific surgery education video domain, our technique achieves overall \approx 87:3% accuracy for four pre-defined semantic medical events.

关键词： Medical diagnostic imaging Skin Surgery Biomedical imaging Event detection Visualization Object detection

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Parametric Subpixel Matchpoint Recovery with Uncertainty Estimation: A Statistical Approach

Parametric Subpixel Matchpoint Recovery with Uncertainty Est...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Matt Steele Christopher Jaynes Department of Computer Science University of Kentucky Lexington KY USA

We present a novel matchpoint acquisition method capable of producing accurate correspondences at subpixel precision. Given the known representation of the point to be matched, such as a projected fiducial in a structured light system, the method estimates the fiducial location and its expected uncertainty. Improved matchpoint precision has application in a number of calibration tasks, and uncertainty estimates can be used to significantly improve overall calibration results. A simple parametric model captures the relationship between the known fiducial and its corresponding position, shape, and intensity on the image plane. For each match-point pair, these unknown model parameters are recovered using maximum likelihood estimation to determine a sub-pixel center for the fiducial. The uncertainty of the match-point center is estimated by performing forward error analysis on the expected image noise. Uncertainty estimates used in conjunction with the accurate matchpoints can improve calibration accuracy for multi-view systems.

关键词： Accuracy Cameras Pixel Mathematical model Equations Uncertainty Calibration

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Appearance-based Tracking of Persons with an Omnidirectional vision Sensor

Appearance-based Tracking of Persons with an Omnidirectional...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Grzegorz Cielniak Mihajlo Miladinovic Daniel Hammarin Linus Goranson Achim Lilienthal Tom Duckett Department of Technology AASS Örebro University Orebro Sweden W.-Schickard-Institute for Computer Science University of Tübingen Tubingen Germany

This paper addresses the problem of tracking a moving person with a single, omnidirectional camera. An appearance-based tracking system is described which uses a self-acquired appearance model and a Kalman filter to estimate the position of the person. Features corresponding to "depth cues" are first extracted from the panoramic images, then an artificial neural network is trained to estimate the distance of the person from the camera. The estimates are combined using a discrete Kalman filter to track the position of the person over time. The ground truth information required for training the neural network and the experimental analysis was obtained from another vision system, which uses multiple webcams and triangulation to calculate the true position of the person. Experimental results show that the tracking system is accurate and reliable, and that its performance can be further improved by learning multiple, person-specific appearance models.

关键词： Cameras Robots Robot sensing systems Distance measurement Artificial neural networks Robot vision systems Kalman filters

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Image Based Hand Tracking via Interacting Multiple Model and Probabilistic Data Association (IMM-PDA) Algorithm

Image Based Hand Tracking via Interacting Multiple Model and...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Shunguang Wu Lang Hong Francis Quek Department of Electrical Engineering Wright State University Dayton OH USA Departmentof Computer Science and Engineering Wright State University Dayton OH USA

Traditional image based hand tracking uses a single Kalman filter to estimate and predict the hand state (position, velocity, and acceleration). However, this approach may fail in the case of large maneuvers and cluttered measurements. In this paper we propose to use the interacting multiple model (IMM) filter to catch a maneuver and the probabilistic data association (PDA) method to process noisy measurements and false alarms. A theoretical framework of image based hand tracking by IMM-PDA is set up. Experiment results from several video segments show that IMM-PDA can successfully track hand motions in a natural conversational environment.

关键词： Mathematical model Noise Noise measurement Time measurement Computational modeling Position measurement Covariance matrix

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