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Dive into the research topics where Camillo J. Taylor is active.

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Featured researches published by Camillo J. Taylor.


international conference on computer graphics and interactive techniques | 1996

Modeling and rendering architecture from photographs: a hybrid geometry- and image-based approach

Paul E. Debevec; Camillo J. Taylor; Jitendra Malik

We present a new approach for modeling and rendering existing architectural scenes from a sparse set of still photographs. Our modeling approach, which combines both geometry-based and imagebased techniques, has two components. The first component is a photogrammetricmodeling method which facilitates the recovery of the basic geometry of the photographed scene. Our photogrammetric modeling approach is effective, convenient, and robust because it exploits the constraints that are characteristic of architectural scenes. The second component is a model-based stereo algorithm, which recovers how the real scene deviates from the basic model. By making use of the model, our stereo technique robustly recovers accurate depth from widely-spaced image pairs. Consequently, our approach can model large architectural environments with far fewer photographs than current image-based modeling approaches. For producing renderings, we present view-dependent texture mapping, a method of compositing multiple views of a scene that better simulates geometric detail on basic models. Our approach can be used to recover models for use in either geometry-based or image-based rendering systems. We present results that demonstrate our approach’s ability to create realistic renderings of architectural scenes from viewpoints far from the original photographs. CR Descriptors: I.2.10 [Artificial Intelligence]: Vision and Scene Understanding Modeling and recovery of physical attributes; I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism Color, shading, shadowing, and texture I.4.8 [Image Processing]: Scene Analysis Stereo; J.6 [Computer-Aided Engineering]: Computer-aided design (CAD).


international conference on robotics and automation | 2002

A vision-based formation control framework

Aveek K. Das; Rafael Fierro; R. Vijay Kumar; James P. Ostrowski; John R. Spletzer; Camillo J. Taylor

The invention relates to a rack for electronic plug-in units, comprising a backplane. The backplane comprises at least one connector to which a connector provided in the electronic plug-in unit connects when the plug-in unit is pushed into the rack. The backplane is attached to the rack with a fastener made of a resilient material. A moment arm is formed between a point which attaches the fastener to the rack and the backplane. When the plug-in unit is pushed into the rack, there is a tolerance for alignment of the connectors enabling connection of the connectors. Furthermore, when the plug-in unit is in the rack, the mobility of the backplane prevents the connectors and/or the backplane from breaking as the rack moves.


Computer Vision and Image Understanding | 2000

Reconstruction of Articulated Objects from Point Correspondences in a Single Uncalibrated Image

Camillo J. Taylor

This paper investigates the problem of recovering information about the configuration of an articulated object, such as a human figure, from point correspondences in a single image. Unlike previous approaches, the proposed reconstruction method does not assume that the imagery was acquired with a calibrated camera. An analysis is presented which demonstrates that there is a family of solutions to this reconstruction problem parameterized by a single variable. A simple and effective algorithm is proposed for recovering the entire set of solutions by considering the foreshortening of the segments of the model in the image. Results obtained by applying this algorithm to real images are presented.


IEEE Transactions on Pattern Analysis and Machine Intelligence | 1995

Structure and motion from line segments in multiple images

Camillo J. Taylor; David J. Kriegman

This paper presents a new method for recovering the three dimensional structure of a scene composed of straight line segments using the image data obtained from a moving camera. The recovery algorithm is formulated in terms of an objective function which measures the total squared distance in the image plane between the observed edge segments and the projections (perspective) of the reconstructed lines. This objective function is minimized with respect to the line parameters and the camera positions to obtain an estimate for the structure of the scene. The effectiveness of this approach is demonstrated quantitatively through extensive simulations and qualitatively with actual image sequences. The implementation is being made publicly available. >


The International Journal of Robotics Research | 2005

Control of a Quadrotor Helicopter Using Dual Camera Visual Feedback

Erdinç Altuğ; Jim Ostrowski; Camillo J. Taylor

In this paper we propose a vision-based stabilization and output tracking control method for a model helicopter. A novel two-camera method is introduced for estimating the full six-degrees-of-freedom pose of the helicopter. One of these cameras is located on-board the helicopter, and the other camera is located on the ground. Unlike previous work, these two cameras are set to see each other. The pose estimation algorithm is compared in simulation to other methods and is shown to be less sensitive to errors on feature detection. In order to build an autonomous helicopter, two methods of control are studied: one using a series of mode-based, feedback linearizing controllers and the other using a backstepping-like control law. Various simulations demonstrate the implementation of these controllers. Finally, we present flight experiments where the proposed pose estimation algorithm and non-linear control techniques have been implemented on a remote-controlled helicopter.


The International Journal of Robotics Research | 1999

A Comparative Study of Vision-Based Lateral Control Strategies for Autonomous Highway Driving:

Camillo J. Taylor; Jana Kosecka; Robert Blasi; Jitendra Malik

With the increasing speeds of modern microprocessors, it has become ever more common for computer-vision algorithms to find application in real-time control tasks. In this paper, we present an analysis of the problem of steering an autonomous vehicle along a highway based on the images obtained from a CCD camera mounted in the vehicle. We explore the effects of changing various important system parameters like the vehicle velocity, the look-ahead range of the vision sensor, and the processing delay associated with the perception and control systems. We also present the results of a series of experiments that were designed to provide a systematic comparison of a number of control strategies. The control strategies that were explored include a lead-lag control law, a full-state linear controller, and an input-output linearizing control law. Each of these control strategies was implemented and tested at highway speeds on our experimental vehicle platform, a Honda Accord LX sedan.


international conference on robotics and automation | 2003

Quadrotor control using dual camera visual feedback

Erdinç Altuğ; James P. Ostrowski; Camillo J. Taylor

In this paper, a vision-based stabilization and output tracking control method for a four-rotor helicopter has been proposed. A novel 2 camera method has been described for estimating the full 6 DOF pose of the helicopter. This two camera system is consisting of a pan-tilt ground camera and an onboard camera. The pose estimation algorithm is compared in simulation to other methods (such as four point method, and a stereo method) and is shown to be less sensitive to feature detection errors on the image plane. The proposed pose estimation algorithm and non-linear control techniques have been implemented on a remote controlled quadrotor helicopter.


Journal of Field Robotics | 2008

Maintaining network connectivity and performance in robot teams

M. Ani Hsieh; Anthony Cowley; R. Vijay Kumar; Camillo J. Taylor

In this paper, we present an experimental study of strategies for maintaining end-to-end communication links for tasks such as surveillance, reconnaissance, and target search and identification, where team connectivity is required for situational awareness. Our main contributions are threefold: (a) We present the construction of a radio signal strength map that can be used to plan multi-robot tasks, and also serve as useful perceptual information. We show how a nominal model of an urban environment obtained by aerial surveillance, is used to generate strategies for exploration. (b) We present reactive controllers for communication link maintenance; and (c) we consider the differences between monitoring signal strength versus data throughput. Experimental results, obtained using our multi-robot testbed in three representative urban environments are presented with each of our main contributions.


international conference on robotics and automation | 2001

Real-time vision-based control of a nonholonomic mobile robot

Aveek K. Das; Rafael Fierro; R. Vijay Kumar; Ben Southall; John R. Spletzer; Camillo J. Taylor

This paper considers the problem of vision-based control of a nonholonomic mobile robot. We describe the design and implementation of real-time estimation and control algorithms on a car-like robot platform using a single omni-directional camera as a sensor without explicit use of odometry. We provide experimental results for each of these vision-based control objects. The algorithms are packaged as control modes and can be combined hierarchically to perform higher level tasks involving multiple robots.


Journal of Field Robotics | 2007

Adaptive Teams of Autonomous Aerial and Ground Robots for Situational Awareness

M. Ani Hsieh; Anthony Cowley; James F. Keller; Luiz Chaimowicz; Ben Grocholsky; Vijay Kumar; Camillo J. Taylor; Yoichiro Endo; Ronald C. Arkin; Boyoon Jung; Denis F. Wolf; Gaurav S. Sukhatme; Douglas C. MacKenzie

This is a preprint of an article accepted for publication in the Journal of Field Robotics, copyright 2007. Journal of Field Robotics 24(11), 991–1014 (2007)

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Vijay Kumar

University of Pennsylvania

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Anthony Cowley

University of Pennsylvania

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R. Vijay Kumar

University of Pennsylvania

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Jitendra Malik

University of California

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Aveek K. Das

University of Pennsylvania

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James F. Keller

University of Pennsylvania

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Sang-Hack Jung

University of Pennsylvania

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Luiz Chaimowicz

Universidade Federal de Minas Gerais

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