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 w...
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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.
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 se...
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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.
A fundamental problem in computervision 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 identica...
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A fundamental problem in computervision 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.
作者:
W. Abd-AlmageedC.E. SmithRobotics
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 u...
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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.
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 migh...
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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.
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 histogram...
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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.
Large vision infrastructures have been installed, or are under construction in many major metropolitan areas. These networks of cameras offer enormous volumes of data from large areas. However, most work in ITS comput...
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ISBN:
(纸本)0769511716
Large vision infrastructures have been installed, or are under construction in many major metropolitan areas. These networks of cameras offer enormous volumes of data from large areas. However, most work in ITS computervision is constricted to the use of either single cameras, or small numbers of cameras. There is an enormous amount of information available from the fusion of data from multiple cameras that is not available from any single sensor. This paper presents an algorithm that provides an example of such data fusion: maintaining the identity of a vehicle, or groups of vehicles as they pass through multiple cameras sites. The algorithm uses a combination of color features and the spatial organization of vehicles within platoons to minimize false positives. The algorithm could be used in an application to track individual cars as they travel long distances through a traffic system allowing the measurement of point-to-point traffic parameters, such as travel time.
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 ...
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ISBN:
(纸本)0769512720
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 traveled by the robot.
Recent innovations in real-time machine vision, distributed computing, software architectures and high-speed communication are expanding the available technology for intelligent system development. These technologies ...
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Recent innovations in real-time machine vision, distributed computing, software architectures and high-speed communication are expanding the available technology for intelligent system development. These technologies allow the realization of intelligent systems that provide the capabilities for a user to experience events from remote locations in an interactive way. In this paper, we describe research aimed at the realization of a powerful televiewing system applied to the traffic incident detection and monitoring needs of today's highways. Sensor clusters utilizing both rectilinear and omni-directional cameras provide an interactive, real-time, multi-resolution televiewing interface to emergency response crews. Ultimately, this system will have a direct impact on reducing incident-related highway congestion by improving the quality of information to which emergency personnel have access.
Robot control in nonlinear and nonstationary run-time environments presents challenges to traditional software methodologies. In particular, robot systems in "open" domains can only be modeled probabilistica...
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