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Pedestrian tracking from a stationary camera using active deformable models

Pedestrian tracking from a stationary camera using active de...

引用

IEEE Symposium on Intelligent Vehicle

作者： M.J. Sullivan C.A. Richards C.E. Smith O. Masoud N.P. Papanikolopoulos Artificial Intelligence Department of Computer Science Robotics and Vision Laboratory University of Minnesota Minneapolis MN USA

The system proposed in this paper uses active deformable models to track pedestrians moving in dynamic real-world scenes. First, figure pixels are separated from a fixed or slowly evolving ground image. Then, an initial segmentation process identifies interesting pixel blobs for tracking. The output of the segmentation process is used to choose the starting position of the control points of the active deformable model. Once tracking has begun, the control points are updated at frame rates by minimizing an energy function involving the relative position of model points, image data, and the characteristics of figure pixels.

关键词： Cameras Deformable models Biological system modeling Layout Humans Motion analysis computer vision Dynamic programming Leg Legged locomotion

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vision-based intelligent control of transportation systems

Vision-based intelligent control of transportation systems

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IEEE International Symposium on Intelligent Control (ISIC)

作者： C.A. Richards C.E. Smith N.P. Papanikolopoulos Artificial Intelligence Robotics and Vision Laboratory Department of Computer Science University of Minnesota Minneapolis MN USA

In response to the overcrowding of transportation systems, there has been an increase in the emphasis placed upon intelligent vehicle/highway systems (IVHS). Whether the application is keeping a safe distance between vehicles on highways or allowing a pedestrian to safely cross a street, environmental sensing and control play a crucial role in IVHS applications. In this paper we present robust visual detection and tracking techniques for IVHS applications, where computer vision may be the only sensor used or a part of a larger multi-sensor system. We have selected the application of pedestrian detection and tracking to demonstrate that the controlled active vision framework can provide precisely the type of information required to effectively manage traffic situations.

关键词： Intelligent control Intelligent transportation systems Application software Road transportation Intelligent vehicles Road vehicles Vehicle safety Robustness computer vision Sensor systems and applications

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The automatic detection and visual tracking of moving objects by eye-in-hand robotic systems

The automatic detection and visual tracking of moving object...

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Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots

作者： C.A. Richards N.P. Papanikolopoulos Artificial Intelligence Robotics and Vision Laboratory Department of Computer Science University of Minnesota Minneapolis MN USA

Traditionally, the robotic visual servoing/tracking problem has received attention from researchers for its interesting control and computer vision issues. However many visual servoing tasks also require the ability to automatically detect moving objects. Until recently, very few efforts have been reported in the area of automatic detection of servoing targets. This paper presents a robust detection scheme for use in robotic visual servoing experiments. It detects and tracks moving objects through the use of a "figure/ground" approach. Experimentation has shown the feasibility of this approach under general conditions. This paper provides a description of the authors system implementation in an experimental robotic system, along with a collection of results. The paper also contains a discussion of problems and issues for future work.

关键词： Object detection robotics and automation Visual servoing Robot vision systems Intelligent robots Robot sensing systems Target tracking Automatic control Feedback loop Adaptive control

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Grasping of static and moving objects using a vision-based control approach

Grasping of static and moving objects using a vision-based c...

引用

IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： C.E. Smith N.P. Papanikolopoulos Artificial Intelligence Robotics and Vision Laboratory Department of Computer Science University of Minnesota Minneapolis MN USA

Recent work combining robotics with vision has emphasized an active vision paradigm where the system changes the pose of the camera to improve environmental knowledge or to establish and presence a desired relationship between the robot and objects in the environment. Much of this work has concentrated upon the active observation of objects by the robotic agent. In this paper we present extensions to the controlled active vision framework that focus upon the autonomous grasping of a moving or static object in the manipulator's workspace. Our work extends the capabilities of an eye-in-hand system beyond those as a "pointer" or a "camera orienter" to provide the flexibility required to robustly interact with the environment in the presence of uncertainty. The proposed work is experimentally verified using the Minnesota robotic visual tracker to automatically select object features, to derive estimates of unknown environmental parameters, and to supply a control vector based upon these estimates to guide the manipulator in the grasping of a moving or static object.

关键词： Robot sensing systems Robot vision systems Cameras Manipulators Intelligent robots Grippers Charge-coupled image sensors Artificial intelligence Laboratories computer science

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A system for automatically detecting and tracking objects using a visually-guided manipulator

A system for automatically detecting and tracking objects us...

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IEEE International Conference on Systems, Man and Cybernetics

作者： C.A. Richards N.P. Papanikolopoulos Artificial Intelligence Robotics and Vision Laboratory Department of Computer Science University of Minnesota Minneapolis MN USA Department of Computer Science University of Stanford Stanford CA USA

This paper presents a framework for the automatic visual detection of moving objects in robotic servoing tasks. The paper describes a "figure/ground" scheme which is able to perform detection without making many assumptions that would limit the generality of the approach. We describe optimizations which allow for real-time execution of the frame-differencing that is the basis of our framework. Experimentation has demonstrated that the results of the visual detection can provide information helpful in focusing attention on a specific subset of objects. Furthermore, we show how the detection technique can be integrated with existing methods for visual tracking. We mention some details that have been addressed in order to apply these theories to an actual robotic system, including the use of an optimal controller Our paper explains how this framework has been implemented in our experimental robotic system MRVT, and it describes several results obtained from this experimentation.

关键词： Object detection Pixel robotics and automation Manipulators Intelligent robots Robot vision systems computer science Visual servoing Optical computing Artificial intelligence

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Sensorless manipulation using transverse vibrations of a plate

Sensorless manipulation using transverse vibrations of a pla...

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IEEE International Conference on robotics and Automation (ICRA)

作者： K.-F. Bohringer V. Bhatt K.Y. Goldberg Robotics & Vision Laboratory Department of Computer Science Cornell University Ithaca NY USA Sibley School of Mechanical and AeroSpace Engineering Cornell University Ithaca NY USA Department of Computer Scienc University of Southern California Los Angeles CA USA

The existing industrial parts feeders move the parts through a sequence of mechanical filters that reject parts in unwanted orientations. In this paper we develop a new setup that uses a different vibratory mechanism to systematically manipulate parts, by actively orienting and localizing them. The idea is to generate and change dynamic modes for a plate by varying the applied frequency of oscillation. Depending on the node shapes of the plate for these frequencies, the position and orientation of the parts can be controlled. We develop an analysis of the underlying dynamics, and show that it can be used to predict the behavior of objects placed on the vibrating plate. Using this analysis, we propose that the applied frequencies can be automatically sequenced to obtain a "sensorless" strategy for manipulating a given object.

关键词： Filters Frequency Sensor systems Vibrations computer science Aerodynamics Shape control Assembly Costs Tactile sensors

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Using vision-based control techniques for grasping objects

Using vision-based control techniques for grasping objects

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IEEE International Conference on Systems, Man and Cybernetics

作者： C.E. Smith N.P. Papanikolopoulous Artificial Intelligence Robotics and Vision Laboratory Department of Computer Science University of Minnesota Minneapolis MN USA University of Minnesota Minneapolis MN US Dept. of Comput. Sci. Minnesota Univ. Minneapolis MN USA

We present additions to the controlled active vision framework that focus upon the autonomous grasping of a moving object in the manipulator's workspace. Our work extends the capabilities of an eye-in-hand robotic system beyond those as a "pointer" or a "camera orienter" to provide the flexibility required to robustly interact with the environment in the presence of uncertainty. The proposed work is experimentally verified using the Minnesota Robotic Visual Tracker (MRVT) to automatically select object features, to derive estimates of unknown environmental parameters, and to supply a control vector based upon these estimates to guide the manipulator in the grasping of a moving object. The system grasps objects in the manipulator's workspace without requiring the object to follow a specific trajectory and without requiring the object to maintain a specific orientation.

关键词： Robot vision systems Manipulators robotics and automation Cameras Grippers Robustness Uncertainty Automatic control Optical distortion Artificial intelligence

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Analyzing teams of cooperating mobile robots

Analyzing teams of cooperating mobile robots

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IEEE International Conference on robotics and Automation (ICRA)

作者： B.R. Donald J. Jennings D. Rus Robotics & Vision Laboratory Computer Science Department Cornell University Ithaca NY USA

Donald (1993) described a manipulation task for cooperating mobile robots that can push large, heavy objects. There, the author asked whether explicit local and global communication between the agents can be removed from a family of pushing protocols. In this paper, the authors answer in the affirmative. They do so by using the general methods of Donald for analyzing information invariants. The authors discuss several measures for the information complexity of the task of pushing with cooperating mobile robots, and they present a methodology for creating new manipulation strategies out of existing ones. The authors develop and analyze synchronous and asynchronous manipulation protocols for a small team of cooperating mobile robots than can push large boxes. The protocols described have been implemented in several forms on the Cornell mobile robots in the authors' laboratory.< >

关键词： Mobile robots Robot kinematics Robot sensing systems Protocols Laboratories Information analysis Friction Manipulator dynamics Robot vision systems computer science

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Off-line recognition of signatures using revolving active deformable models

Off-line recognition of signatures using revolving active de...

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IEEE International Conference on Systems, Man and Cybernetics

作者： I. Pavlidis R. Mavuduru N. Papanikolopoulos Artificial Intelligence Robotics and Vision Laboratory Department of Computer Science University of Minnesota Minneapolis MN USA

This paper presents a novel approach to the problem of signature recognition. We introduce the use of revolving active deformable models as a powerful way of capturing the unique characteristics of a signature's silhouette. Experimental evidence shows that the silhouette of a signature uniquely determines the signature in the majority of cases. The objective of our method is to recognize signatures based on the spatial properties of the signature boundaries. Our active deformable models originate from the snakes introduced to computer vision by Kass et al. (1987), but their implementation has been tailored to the task at hand. These computer-generated models interact with the virtual gravity field created by the image gradient. Ideally, the uniqueness of this interaction mirrors the uniqueness of the signature's silhouette. The proposed method obviates the use of a computationally expensive segmentation approach and yields satisfactory results regarding performance, without compromising the accuracy rate. Interestingly, the active deformable models have been implemented in such a way, that the method is potentially fully parallelizable. The experiments performed with a signature database show that the proposed method is promising.< >

关键词： Deformable models Databases Character recognition Handwriting recognition Artificial intelligence Intelligent robots Robot vision systems Laboratories computer science computer vision

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Computation of shape through controlled active exploration

Computation of shape through controlled active exploration

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IEEE International Conference on robotics and Automation (ICRA)

作者： C.E. Smith N.P. Papanikolopoulos Artificial Intelligence Robotics and Vision Laboratory Department of Computer Science University of Minnesota Minneapolis MN USA

Accurate knowledge of depth continues to be of critical importance in robotic systems. Without accurate depth knowledge, tasks such as inspection, tracking, grasping, and collision-free motion planning prove to be difficult and often unattainable. Traditional visual depth recovery has relied upon techniques that require the solution of the correspondence problem or require known lighting conditions and Lambertian surfaces. In this paper, we present a technique for the derivation of depth from feature points on a target's surface using the controlled active vision framework. We use a single visual sensor mounted on the end-effector of a robotic manipulator to automatically select feature points and to derive depth estimates for those features using adaptive control techniques. Movements of the manipulator produce displacements that are measured using a sum-of-squared difference (SSD) optical flow. The measured displacements are fed into the controller to alter the path of the manipulator and to refine the depth estimate.< >

关键词： Shape control Manipulators Automatic control Displacement measurement Inspection Tracking Motion planning Sensor phenomena and characterization Robot sensing systems robotics and automation

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