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International Conference on Digital Signal Processing (DSP)

作者： H. Veeraraghavan O. Masoud N. Papanikolopoulos Artificial Intelligence Vision and Robotics Lab Department of Computer Science and Engineering University of Minnesota USA

The goal of this project is to develop a passive vision-based sensing system capable of monitoring an intersection by observing the vehicle and pedestrian flow, and predicting situations that might give rise to accidents. A single camera mounted at an arbitrary position looking at an intersection is used. However, for extended applications multiple cameras will be needed. Some of the key elements are camera calibration, motion tracking, vehicle classification, and predicting collisions. In this paper, we focus on motion tracking. Motion segmentation is performed using an adaptive background model that models each pixel as a mixture of Gaussians. The method used is similar to the Stauffer method for motion segmentation. Tracking of objects is performed by computing the overlap between oriented bounding boxes. The oriented boxes are computed by vector quantization of blobs in the scene. The principal angles computed during vector quantization along with other cues of the object are used for classification of detected entities into vehicles and pedestrians.

关键词： Cameras Tracking Motion segmentation computer vision Vector quantization Vehicle detection Monitoring Accidents Calibration Gaussian processes

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A novel interactivity environment for integrated intelligent transportation and telematic systems

A novel interactivity environment for integrated intelligent...

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International Conference on Intelligent Transportation

作者： T.B. Hall M.A. Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego La Jolla CA USA

Advances in intelligent transportation are rapidly sensing and connecting both highways and vehicles. This recent availability of high-speed communication and large quantities of information are rapidly changing the way we perceive transportation. In order to develop technologies and applications that are practical in this intelligent environment, it is important to consider specific ways to best use this infrastructure effectively. This paper focuses on the development of and experiments with a visualization environment that presents an interactive, immersive, and context-preserving display of outdoor information. The developed visualization integrates a variety of types of information about a section of interstate such as aerial photographs, maps, and live outdoor videos into a single interactive environment. Additionally, a wireless mobile testbed is presented that allows the undertaking of novel interactivity experiments among mobile participants without requiring a fully instrumented vehicle. These systems allow effective experimentation with and integration between highway and vehicle based real-world intelligent transportation systems.

关键词： Intelligent transportation systems Telematics Intelligent vehicles Road transportation Road vehicles Visualization Joining processes Displays Videos Testing

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Distributed interactive video arrays for event based analysis of incidents

Distributed interactive video arrays for event based analysi...

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International Conference on Intelligent Transportation

作者： M.M. Trivedi A. Prati G. Kogut Computer Vision and Robotics Research Laboratory University of California San Diego La Jolla CA USA

The distributed interactive video array (DIVA) system is developed to provide a large-scale, redundant cluster of video streams to observe a remote scene and to supply automatic focus-of-attention with event-driven servoing to capture desired events at appropriate resolutions and perspectives. Installing multiple sensors introduces several new research issues related to the system design, including handoff schemes for passing tracked objects between sensors and clusters, methods for determining the "best view" given the context of the traffic scene, and sensor fusion algorithms to best employ the strengths of a given sensor or sensor modality. This paper describes our research focused on the development of DIVA system for traffic and incident monitoring. The paper describes the overall architecture of the DIVA system. Algorithms for vehicle and platoon tracking using multiple cameras, and experimental results using novel distributed video networks deployed on the campus and the interstate I-5.

关键词： Sensor fusion Sensor systems Layout Large-scale systems Streaming media Clustering algorithms Telecommunication traffic Monitoring Vehicles Cameras

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On the way to solve lighting problems in underwater imaging

On the way to solve lighting problems in underwater imaging

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OCEANS

作者： R. Garcia T. Nicosevici X. Cufi Computer Vision and Robotics Group Institute of Informatics and Applications E.P.S. University of Girona Girona Spain

A major obstacle to processing images of the ocean floor comes from the absorption and scattering effects of the light in the aquatic environment. Due to the absorption of the natural light, underwater vehicles often require artificial light sources attached to them to provide the adequate illumination. Unfortunately, these flashlights tend to illuminate the scene in a nonuniform fashion, and, as the vehicle moves, induce shadows in the scene. For this reason, the first step towards application of standard computer vision techniques to underwater imaging requires dealing first with these lighting problems. This paper analyses and compares existing methodologies to deal with low-contrast, nonuniform illumination in underwater image sequences. The reviewed techniques include: (i) study of the illumination-reflectance model, (ii) local histogram equalization, (iii) homomorphic filtering, and, (iv) subtraction of the illumination field. Several experiments on real data have been conducted to compare the different approaches.

关键词： Lighting Absorption Layout Oceans Light scattering Underwater vehicles Light sources Application software computer vision Image analysis

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Contour migration: solving object ambiguity with shape-space visual guidance

Contour migration: solving object ambiguity with shape-space...

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IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： W. Abd-Almageed C.E. Smith Department of Electrical and Computer Engineering Robotics Artificial Intelligence and Vision Laboratory University of New Mexico Albuquerque NM USA

A fundamental problem in computer vision is the issue of shape ambiguity. Simply stated, a silhouette cannot uniquely identify an object or an object's classification since many unique objects can present identical occluding contours. This problem has no solution in the general case for a monocular vision system. This paper presents a method for disambiguating objects during silhouette matching using a visual servoing system. This method identifies the camera motion(s) that gives disambiguating views of the objects. These motions are identified through a new technique called contour migration. The occluding contour's shape is used to identify objects or object classes that are potential matches for that shape. A contour migration is then determined that disambiguates the possible matches by purposive viewpoint adjustment. The technique is demonstrated using an example set of objects.

关键词： Shape Cameras computer vision Object recognition Machine vision Databases Intelligent robots Robot vision systems Artificial intelligence Laboratories

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Mixture models for dynamic statistical pressure snakes

Mixture models for dynamic statistical pressure snakes

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International Conference on Pattern Recognition

作者： W. Abd-Almageed C.E. Smith Robotics Artificial Intelligence and Vision Laboratory Electrical and Computer Engineering Department University of New Mexico Albuquerque NM USA

This paper introduces a new approach to statistical pressure snakes. It uses statistical modeling for both object and background to obtain a more robust pressure model. The Expectation Maximization (EM) algorithm is used to model the data into a Mixture of Gaussians (MoG). Bayesian theory is then employed as a decision making mechanism. Experimental results using the traditional pressure model and the new mixture pressure model demonstrate the effectiveness of the new models.

关键词： Image edge detection computer vision Equations Robot vision systems Robustness Bayesian methods Active contours Gaussian distribution Intelligent robots Artificial intelligence

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vision-based monitoring of intersections

Vision-based monitoring of intersections

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International Conference on Intelligent Transportation

作者： H. Vceraraghavan O. Masoud N. Papanikolopoulos Artificial Intelligence University of Minnesota Vision and Robotics Laboratory Department of Computer Science and Engineering Artificial Intelligence University of Minnesota USA

The goal of tills project Is to develop a passive vision-based sensing system. The system will be capable of monitoring an intersection by observing the vehicle and pedestrian flow, and predicting situations that might give rise to accidents. A single camera looking at all intersection from an arbitrary position is used. However, for extended applications, multiple cameras will be needed. Some of the key elements are camera calibration, motion tracking, vehicle classification, and situations giving rise to collisions. In this paper, we focus on motion tracking. Motion segmentation is performed using an adaptive background model that models each pixel as a mixture of Gaussians. The method used is similar to the method of Stauffer et at. for motion segmentation. Tracking of objects is performed by computing the overlap between oriented bounding boxes. The oriented boxes are computed by vector quantization of the blobs in the scene. The principal angles computed during vector quantization along with other cues of the object are used for classification of detected entities into vehicles and pedestrians.

关键词： Monitoring Cameras Tracking Motion segmentation computer vision Vector quantization Vehicle detection Accidents Calibration Gaussian processes

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2-D VISUAL SERVOING WITH INTEGRATION OF MULTIPLE PREDICTIONS OF MOVEMENT BASED ON KALMAN FILTER

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IFAC Proceedings Volumes 2002年第1期35卷 25-29页

作者： Jorge Pomares Baeza Fernando Torres Medina Pablo Gil Vázquez Automatics Robotics and Computer Vision Group (http://www.disc.ua.es/gava) Physic Systems Engineering and Signal Theory Department University of Alicante Crtra. San Vicente s/n 03080 Alicante

In this paper, a visual servoing for the tracking of objects in a plane using a fixed camera system is shown. The method proposed of tracking makes use of a variable number of trackers determined automatically. The integration of the predictions of each of them affords a flexible and robust system of tracking. The studies of efficiency carried out reflect that the delays produced are suitable for use in visual servoing. The proposed system can be generalized to tracking three-dimensional objects with movable cameras.

关键词： Tracking Visual motion Automatic control (closed-loop) Delay analysis Estimation algorithms Image processing Prediction methods

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Robot homing based on corner tracking in a sequence of panoramic images

Robot homing based on corner tracking in a sequence of panor...

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2001 IEEE computer Society Conference on computer vision and Pattern Recognition

作者： Argyros, Antonis A. Bekris, Kostas E. Orphanoudakis, Stelios C. Computer Vision and Robotics Lab. Institute of Computer Science Found. for Res./Technology - Hellas Heraklion Crete Greece

In robotics, homing can be defined as that behavior which enables a robot to return to its initial (home) position, after traveling a certain distance along an arbitrary path. Odometry has traditionally been used for the implementation of such a behavior, but it has been shown to be an unreliable source of information. In this work, a novel method for visual homing is proposed, based on a panoramic camera. As the robot departs from its initial position, it tracks characteristic features of the environment (corners). As soon as homing is activated, the robot selects intermediate target positions on the original path. These intermediate positions (IPs) are then visited sequentially, until the home position is reached. For the robot to move between two consecutive IPs, it is only required to establish correspondence among at least three corners. This correspondence is obtained through a feature tracking mechanism. The proposed homing scheme is based on the extraction of very low-level sensory information, namely the bearing angles of corners, and has been implemented on a robotic platform. Experimental results show that the proposed scheme achieves homing with a remarkable accuracy, which is not affected by the distance travelled by the robot.

关键词： robotics

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Fast Landmark Tracking and Localization Algorithm for the Mobile Robot Self-Localization

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IFAC Proceedings Volumes 2001年第4期34卷 185-190页

作者： Kuk-Jin Yoon Gi-Jeong Jang Sung-Ho Kim In-So Kweon Robotics and Computer Vision Laboratory Dept. of Electrical Engineering and Computer Science KAIST Korea

We present a simple artificial landmark model and a robust landmark tracking alg orithm for mobile robot localization. The landmark model, consisting of symmetric and repetitive color patches, produces color histograms that are invariant under the geometric and photometric distortions. A stochastic approach based on the CONDENSATION tracks the landmark model robustly even under the varying illumination conditions. After the landmark detection, relative position of the mobile robot to the landmark is calculated. Experimental results show that the proposed landmark model is effective and can be detected and tracked in a cluttered scenerobustly. The tracked single landmark is enough to detennine the position of the robot.

关键词： tracking applications robot vision

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