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Conference on intelligent robots and computer vision XXII - algorithms, techniques and active vision

作者： Mundhenk, TN Landauer, C Bellman, K Arbib, NA Itti, L Univ So Calif Dept Comp Sci Henry Salvatori Comp Sci Ctr Los Angeles CA 90089 USA

ISBN: (纸本)081945561X

We discus a tool kit for usage in scene understanding where prior information about targets is not necessarily understood. As such, we give it a notion of connectivity such that it can classify features in an image for the purpose of tracking and identification. The tool VFAT (Visual Feature Analysis Tool) is designed to work in real time in an intelligent multi agent room. It is built around a modular design and includes several fast vision processes. The first components discussed are for feature selection using visual saliency and Monte Carlo selection. Then features that have been selected from an image are mixed into useful and more complex features. All the features are then reduced in dimension and contrasted using a combination of Independent Component Analysis and Principle Component Analysis (ICA/PCA). Once this has been done, we classify features using a custom non-parametric classifier (NPclassify) that does not require hard parameters such as class size or number of classes so that VFAT can create classes without stringent priors about class structure. These classes are then generalized using Gaussian regions which allows easier storage of class properties and computation of probability for class matching. To speed up to creation of Gaussian regions we use a system of rotations instead of the traditional Psuedo-inverse method. In addtion to discussing the structure of VFAT we discuss training of the current system which is relatively easy to perform. ICA/PCA is trained by giving VFAT a large number of random images. The ICA/PCA matrix is computed by features extracted by VFAT. The non-parametric classifier NPclasify it trained by presenting it with images of objects having it decide how many objects it thinks it sees. The difference between what it sees and what it is supposed to see in terms of the number of objects is used as the error term and allows VFAT to learn to classify based upon the experimenters subjective idea of good classification.

关键词： iRoom biological vision tool multi agent saliency real time

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An active trinocular vision system for sensing mobile robot navigation environments

An active trinocular vision system for sensing mobile robot ...

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2004 IEEE/RSJ International Conference on intelligent robots and Systems (IROS)

作者： Kim, Min Young Cho, Hyungsuck Lee, Hyunki Department of Mechanical Engineering Korea Adv. Inst. Sci. and Technol. 373-1 Guseong-dong Yuseong-gu Daejeon 305-701 Korea Republic of

ISBN: (纸本)0780384636

intelligent autonomous mobile robots must be able to sense and recognize 3D indoor space where they live or work. In this paper, we propose a new 3D sensing system using the laser structured lighting method, because of its robustness on the nature of the navigation environment and the easy extraction of feature information of interest. The proposed active trinocular vision system is composed of a flexible multi-stripe laser projector and two cameras arranged with a triangular shape. Based on the virtual camera concept and the trinocular epipolar constraints, the matching pairs of line features in two real camera images are established, and 3D information from one-shot image can be extracted on the patterned scene. Especially, for robust line feature matching, we propose a new correspondence matching algorithms based on line grouping and probabilistic voting. Finally, a series of experimental tests is performed to show its efficiency and accuracy.

关键词： computer vision

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active learning for robot manipulation 16

Active learning for robot manipulation

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16th European Conference on Artificial Intelligence, ECAI 2004

作者： Morales, Antonio Chinellato, Eris Fagg, Andrew H. Del Pobil, Angel P. Intelligent Robotics Lab. Univertitat Jaume I Castellon Spain Computer Science Department University of Massachusetts AmherstMA United States

ISBN: (纸本)9781586034528

This paper describes a novel application of active learning techniques in the field of robotic grasping. A vision-based grasping system has been implemented on a humanoid robot. It is able to compute a set of feasible grasps and to execute any of them and measure their actual reliability. An algorithm aimed at predicting the performance of an untested grasp using the results observed on previous similar attempts is presented. The previous experience is stored using a set of vision-based grasp descriptors. Moreover, a second algorithm that actively selects the next grasp to be executed in order to improve the predictive quality of the accumulated experience is introduced. An exhaustive database of experimental data is collected and used to test and validate both algorithms.

关键词： Anthropomorphic robots

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techniques for evaluating optical flow for visual odometry in extreme terrain

Techniques for evaluating optical flow for visual odometry i...

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2004 IEEE/RSJ International Conference on intelligent robots and Systems (IROS) (IEEE Cat. No.04CH37566)

作者： J. Campbell R. Sukthankar I. Nourbakhsh Robotics Institute Carnegie Mellon Pittsburgh PA USA Intel Research Pittsburgh Pittsburgh PA USA NASA Ames Research Center Moffett Field Moffett Field CA USA

Motion vision (visual odometry, the estimation of camera egomotion) is a well researched field, yet has seen relatively limited use despite strong evidence from biological systems that vision can be extremely valuable for navigation. The limited use of such vision techniques has been attributed to a lack of good algorithms and insufficient computer power, but both of those problems were resolved as long as a decade ago. A gap presently yawns between theory and practice, perhaps due to perceptions of robot vision as less reliable and more complex than other types of sensing. We present an experimental methodology for assessing the real world precision and reliability of visual odometry techniques in both normal and extreme terrain. This paper evaluates the performance of a mobile robot equipped with a simple vision system in common outdoor and indoor environments, including grass, pavement, ice, and carpet. Our results show that motion vision algorithms can be robust and effective, and suggest a number of directions for further development.

关键词： Image motion analysis Ultraviolet sources Machine vision Biomedical optical imaging Optical sensors Motion estimation Cameras Biological systems Navigation Biology computing

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Euclidean reconstruction independent on camera intrinsic parameters

Euclidean reconstruction independent on camera intrinsic par...

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IEEE International Workshop on intelligent robots and Systems (IROS)

作者： E. Malis A. Bartoli I.N.R.I.A. Sophia-Antipolis France INRlA Rhone-Alpes France

Standard bundle adjustment techniques for Euclidean reconstruction consider camera intrinsic parameters as unknowns in the optimization process. Obviously, the speed of an optimization process is directly related to the number of unknowns and to the form of the cost function. The scheme proposed in this paper differs from previous standard techniques since unknown camera intrinsic parameters are not considered in the optimization process. Considering fewer unknowns in the optimization process produces a faster algorithm, which is more adapted to time-dependent applications such as robotics. Computationally expensive metric reconstruction, using for example several zooming cameras, considerably benefits from an intrinsics-free bundle adjustment.

关键词： Cameras Image reconstruction Cost function Robot vision systems Computational efficiency Reconstruction algorithms Layout Predictive models computer applications computer vision

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Fast eigenspace decomposition of correlated images using their low-resolution properties

Fast eigenspace decomposition of correlated images using the...

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IEEE International Workshop on intelligent robots and Systems (IROS)

作者： K. Saitwal A.A. Maciejewski R.G. Roberts Department of Electrical and Computer Engineering Colorado State University Fort Collins CO USA Department of Electrical and Computer Engineering Florida A & M Florida State University Tallahassee FL USA

Eigendecomposition is a common technique that is performed on sets of correlated images in a number of computer vision and robotics applications. Unfortunately, the computation of an eigendecomposition can become prohibitively expensive when dealing with very high resolution images. While reducing the resolution of the images will reduce the computational expense, it is not known a priori how this will affect the quality of the resulting eigendecomposition. The work presented here provides an analysis of how different resolution reduction techniques affect the eigendecomposition. A computationally efficient algorithm for calculating the eigendecomposition based on this analysis is proposed. Examples show that this algorithm performs very well on arbitrary video sequences.

关键词： Image resolution Algorithm design and analysis computer vision Application software Image analysis Face detection Pixel Computational efficiency active appearance model Robot vision systems

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Proceedings of SPIE - Intellingent robots and computer vision XXI: algorithms, techniques, and active vision

Proceedings of SPIE - Intellingent Robots and Computer Visio...

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intelligent robots and computer vision XXI: algorithms, techniques, and active vision

The proceedings contains 33 papers from the conference on SPIE - intelligent robots and computer vision XXI: algorithms, techniques, and active vision. The topics discussed include: learning for intelligent mobile robots;remote operation of robotics systems using WLAN- and CORBA-based architecture;autonomous cross-country driving using active vision;Web-based telerobotics system in a virtual reality environment;automatic calibration and neural networks for robot guidance;recursive least squares approach to calculate motion parameters for a moving camera;and effective color representation for image segmentation under nonwhite illumination.

关键词： Robotics

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Rapid omnidirectional vision acquisition using an intelligent linear scanning technique

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MACHINE vision AND APPLICATIONS 2003年第2期14卷 85-93页

作者： Barth, MJ Barrows, C Univ Calif Riverside Dept Elect Engn Riverside CA 92521 USA

Many computer vision applications can benefit from omnidirectional vision sensing, rather than depending solely on conventional cameras that have constrained fields of view. For example, mobile robots often require a full 360degrees. view of their environment in order to perform navigational tasks such identifying landmarks, localizing within the environment, and determining free paths in which to move. There has been much research interest in omnidirectional vision in the past decade and many techniques have been developed. These techniques include: (i) catadioptric methods which can provide rapid image acquisition, but lack image resolution;and (ii) mosaicing and linear scanning techniques which have high image resolution but typically have slow image acquisition speed. In this paper, we introduce a novel linear scanning panoramic vision system that can acquire panoramic images quickly with little loss of image resolution. The system makes use of a fast line-scan camera, instead of a slower, conventional area-scan camera. In addition, a unique coarse-to-fine panoramic imaging technique has been developed that is based on smart sensing principles. Using the active vision paradigm, we control the motion of the rotating camera using feedback from the images. This results in high acquisition speeds and proportionally low storage requirements. Experimentation has been carried out, and results are given.

关键词： omnidirectional vision system linear scanning active vision

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Visual world perception modeling and control of cooperative mobile robots

Visual world perception modeling and control of cooperative ...

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Conference on intelligent robots and computer vision XXI

作者： Shirkhodaie, A Tennessee State Univ Intelligent Tact Mobil Res Lab Dept Mech & Mfg Engn Nashville TN 37209 USA

ISBN: (纸本)081945155X

There has been a great interest in the recent years in visual coordination and target tracking for mobile robots cooperating in unstructured environments. This paper describes visual servo control techniques suitable for intelligent task planning of cooperative robots operating in unstructured environment. In this paper, we have considered a team of semi-autonomous robots controlled by a remote supervisory control system. We have presented an algorithm for visual position tracking of individual cooperative robots within their working environment. Initially, we present a technique suitable for visual servoing of a robot toward its landmark targets. Secondly, we present an image-processing technique that utilizes images from a remote surveillance camera for localization of the robots within the operational environment. In this algorithm, the surveillance camera can be either stationary or mobile. The supervisor control system keeps tracks of relative locations of individual robots and utilizes relative coordinate information of the robots to plan their cooperative activities. We presented some results of this research effort that illustrates effectiveness of the proposed algorithms for cooperative robotic systems visual team working and target tracking.

关键词： world perception modeling cooperative robots robot pose estimation

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Micro-assembly cell with dual optical/computer vision control for electrostatic gripping of MEMS

Micro-assembly cell with dual optical/computer vision contro...

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Conference on intelligent robots and computer vision XXI

作者： Enikov, ET Clark, S Minkov, L Univ Arizona Dept Aeronaut & Mech Engn Tucson AZ 85721 USA

ISBN: (纸本)081945155X

This paper describes the development of a miniature assembly cell for microsystems. The cell utilizes a transparent electrostatic gripper all-owing the use of computer vision for part alignment with respect to the gripper. Part to assembly alignment is achieved via optical triangulation using a fiber-coupled laser and a position sensitive detector (PSD). The system layout, principle of operation and design are described along with the visual and optical control algorithms and their implementation. Experimental measurements of the performance of the stage indicate normal and tangential gripping forces in the range of 0.03-2.5 mN and 1.-9. mN respectively. The visual search algorithm limits the feature tracking speed to 111ms /search. The alignment accuracy of the visual and optical proportional position feedback controls were determined to be +/-7 mum and +/-10 mum respectively.

关键词： electrostatic clamp visual servoing disparate sensing modalities optical feedback

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