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IEEE Workshop on Visualization and Machine vision

作者： S.B. Marapane M.M. Trivedi Computer Vision and Robotics Research Laboratory Department of Electrical and Computer Engineering University of Tennessee Knoxville TN USA

A binocular robot head, BETH, with ten degrees of freedom (DOF) has been developed for research in active vision. To complement BETH, a graphical simulation and visualization environment has also been developed. The objective of building the graphical system is to create a comprehensive design tool to design and study the dynamic behavior of sensory-motor systems and their interactions with the environment. This environment integrates perception and motor actions and features complete kinematic simulation of BETH, it's sensors and it's workspace. We demonstrate the utility of this environment in systematic and extensive experimental development of computational frameworks and algorithms for 3D active vision systems which utilizes multiple passive depth cues (stereo, vergence, and depth from focusing).< >

关键词： Visualization Head Robot sensing systems Robot vision systems computer vision Computational modeling Buildings Focusing Image analysis Machine vision

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Texture segmentation using circular-Mellin operators

Texture segmentation using circular-Mellin operators

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IEEE International Conference on Image Processing

作者： G. Ravichandran M.M. Trivedi Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville TN USA

Texture is an important preattentive cue in region-based segmentation of images. In this paper, we discuss the use of circular-Mellin features for segmenting an image into homogenous regions. The circular-Mellin operators represent the spectral decomposition of the image scene in the polar-log coordinate system and are invariant to both scale and orientation of the target. Coupled with the unique shift invariance property of the correlator architecture, these circular-Mellin operators can be used for rotation- and scale-invariant feature extraction. We note that while both these feature extractors have similar functional form to the Gabor functions, the distortion-invariant characteristics of the circular-Mellin operators make them preferable for texture segmentation. Segmentation results to demonstrate their salient properties are presented.< >

关键词： Image segmentation Layout computer vision Correlators Feature extraction Maximum likelihood detection Filtering theory Gabor filters Nonlinear filters Pattern recognition

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Acquisition of 3D structure of selectable quality from image streams

Acquisition of 3D structure of selectable quality from image...

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IEEE Workshop on Applications of computer vision (WACV)

作者： A.K. Dalmia M. Trivedi Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville TN USA

In this paper we present a computational approach for extracting three-dimensional structure of controllable resolution, depth of field, and accuracy, all made available at real-time speeds. This approach utilizes the spatial and the temporal gradients of the streams of images acquired using an actively controlled camera. Depending on the requirements of a particular task, appropriate parameters such as disparity value sought, the inter-frame camera displacement, and number of frames in a stream, are chosen to control the resolution, depth of field, and accuracy. The acquisition and processing of the image stream are done in real-time on a pipeline architecture based processor. Extensive experiments are presented to demonstrate the accuracy, controllability of depth of field and resolution, and ability to perform successfully in a variety of scenes. The system operated with no latency between the image acquisition and processing. The total acquisition and processing time in these experiments is in the range of 0.27 to 1.56 sec. The depth results have an accuracy of 85% to 92%.< >

关键词： Streaming media computer vision Machine vision Cameras Pipelines Spatial resolution Layout Delay Performance analysis Robot vision systems

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Localized Radon transform-based detection of linear features in noisy images

Localized Radon transform-based detection of linear features...

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IEEE computer Society Conference on computer vision and Pattern Recognition Workshops (CVPRW)

作者： Copeland Ravichandran Trivedi Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville TN USA

This paper presents a Radon transform-based approach to the detection of linear features in images characterized by high noise levels. This approach is based on the localized Radon transform where the intensity integration is performed over short line segments rather than across the entire image. The algorithm, referred to as the feature space line detector (FSLD) algorithm, is tested on synthetic images of linear features with very high noise levels. The results of this testing demonstrate the algorithm's robustness in the presence of noise, as well as its ability to detect and localize linear features that are significantly shorter than the image dimensions or that display some curvature.< >

关键词： Feature extraction

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Real-time visual tracking using correlation techniques

Real-time visual tracking using correlation techniques

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IEEE Workshop on Applications of computer vision (WACV)

作者： M.W. Eklund G. Ravichandran M.M. Trivedi S.B. Marapane Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville TN USA

A real-time correspondence based tracking algorithm is detailed. The system uses a pipeline processor, a general purpose processor, a camera and a display. The Minimum Noise and Correlation Energy (MINACE) filter is used in the tracking algorithm as it provides a good combination of speed, accuracy and flexibility for the targeted hardware system. The system designed is fast and tracking is accomplished at a rate of 15 hz. The system is adaptive and does not rely on a previous model of the object; the training image for filter synthesis is acquired from previous image frames and the filter is synthesized online to accommodate 3-D variations of the target being tracked. The system tracks an object consistently as is demonstrated by the low deviation of the results in the evaluation. The correlation filter-based tracking algorithm has proved to be useful in our research in cooperative mobile robots. A visual servoing system has been implemented using this tracking algorithm for convoying of multiple mobile robots.< >

关键词： Target tracking Cameras Robot vision systems Visual servoing computer vision Adaptive filters Mobile robots Laboratories Power engineering and energy Pipelines

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DARBOUX FRAMES, SNAKES, AND SUPER-QUADRICS - GEOMETRY FROM THE BOTTOM UP

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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 1993年第8期15卷 771-784页

作者： FERRIE, FP LAGARDE, J WHAITE, P Computer Vision and Robotics Laboratory McGill Research Centre of Intelligent Machines Montreal Canada

This paper describes a representation and a computational model for deriving 3-D, articulated, volumetric descriptions of objects from laser rangefinder data. What differentiates this work from other approaches is that it is purely bottom up, relying on general assumptions cast in terms of differential geometry. Darboux frames, snakes, and superquadrics form the basis of this representation, and curvature consistency provides the computational framework. The organization is hierarchical. Darboux frames are used to describe the local surface, whereas snakes are used to interpolate between features, particularly those that serve to partition a surface into its constituent parts. Superquadrics are subsequently used to characterize the 3-D shape of each surface partition. The result is a set of connected volumetric primitives that serve to describe the overall shape of an object. Examples that show how the approach performs on data acquired with a laser rangefinder are included.

关键词： computer vision DIFFERENTIAL GEOMETRY INTERPOLATION PARAMETER ESTIMATION RANGE IMAGE ANALYSIS SCENE ANALYSIS VOLUMETRIC MODELING

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A REAL-TIME IMPLEMENTATION OF STRUCTURE ESTIMATION USING IMAGE STREAMS 6

A REAL-TIME IMPLEMENTATION OF STRUCTURE ESTIMATION USING IMA...

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CONF ON SENSOR FUSION 6

作者： DALMIA, AK TRIVEDI, MM Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville 37996-2100 TN United States

ISBN: (纸本)0819413240

The computation of 3-D structure from motion using a monocular sequence of images in the paradigm of active vision is investigated in this paper. Robotic tasks such as navigation, manipulation, and object recognition all require 3-D description of scene. The 3-D description for these tasks varies in resolution, accuracy, robustness, range, and time. In developing such a system, it must have the capability to actively control the imaging parameters so that a 3-D description sufficient enough for that task is generated. The objective of this paper is to investigate a strategy suitable for fast and active 3-D structure estimation. First, the process of 3-D structure estimation in the paradigm of active vision is discussed. Second, implication of image streams in 3-D structure computation is analyzed. The three approaches to structure from motion, feature based, optical flow based, and spatial and temporal gradient based, are reviewed for their efficacy in fast and active estimation of 3-D structure. Finally, a pipeline based implementation of a spatial and temporal gradient based approach is presented alongwith detailed experimental analysis. © 1993 SPIE. All rights reserved.

关键词： Object recognition

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AN ACTIVE vision SYSTEM FOR DEPTH EXTRACTION USING MULTI-PRIMITIVE HIERARCHICAL STEREO ANALYSIS AND MULTIPLE DEPTH CUES

AN ACTIVE VISION SYSTEM FOR DEPTH EXTRACTION USING MULTI-PRI...

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CONF ON SENSOR FUSION AND AEROSPACE APPLICATIONS

作者： MARAPANE, SB TRIVEDI, MM Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville 37996-2100 TN United States

ISBN: (纸本)0819411922

Binocular stereo, vergence stereo, and depth from focus have been extensively studied in isolation in the past for extraction of depth. These passive approaches have there oivn strengths and limitations. All these cues differ in their input image requirements, computational requirements, and the quality and nature of results they provide. None of them by themselves is sufficient to reliably extract depth information from a wide variety of scenes. It is evident an integrated system ivhich employs multiple cues and exploits their strengths would be most critical for developing a robust depth extraction system. Active vision paradigm alloivs us to develop such a system where various depth cues cooperate to derive the 3-D structure of the scene. In this, the integration would be accomplished by active intelligent control of the acquisition processes tightly coupled to the analysis of image data. One of the uniqueness of our integration approach is that while previous approaches have used a single primitive stereo system, typically edgel based, we have chosen a novel multi-primitive hierarchical(MPH) system. In MPH model, stereo analysis is performed in multiple stages, incorporating multiple primitives, utilizing a hierarchical control strategy. The MPH stereo system consists of three integrated subsystems: region based analysis module;linear edge segment based analysis module;and edgel based stereo analysis module. The use of regions and edge segments in addition to the edgel based analysis add a new dimension to the extraction of depth from stereo images. In fact, even in an integrated multiple cue based system, an edgel based binocular stereo approach alone is insufficient to process a variety of scenes. The reliance of different primitives at various levels makes MPH stereo analysis ideal for use in an integrated multiple cue based depth extraction system. © 1993 SPIE. All rights reserved.

关键词： Extraction

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SAVIC: A SIMULATION, VISUALIZATION AND INTERACTIVE CONTROL ENVIRONMENT FOR MOBILE ROBOTS

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International Journal of Pattern Recognition and Artificial Intelligence 1993年第1期7卷 123-144页

作者： CHUXIN CHEN MOHAN M. TRIVEDI Computer Vision and Robotics Research Laboratory Department of Electrical and Computer Engineering The University of Tennessee Knoxville TN 37996–2100 USA

A Simulation, Animation, Visualization and Interactive Control (SAVIC) environment has been developed for the design and operation of an integrated robotic manipulator system. This unique system possesses the abilities for (1) multi-sensor simulation, (2) kinematics and locomotion animation, (3) dynamic motion and manipulation animation, (4) transformation between real and virtual modes within the same graphics system, (5) ease in exchanging software modules and hardware devices between real and virtual world operations, and (6) interfacing with a real robotic system. This research is focused on enhancing the overall productivity of an integrated human-robot system. This paper describes a working system and illustrates the concepts by presenting the simulation, animation and control methodologies for a unique mobile robot with articulated tracks, a manipulator, and sensory modules.

关键词： Sensor-based robotics intelligent human-machine interface real-time robot simulation sensor simulation visualization virtual reality interactive control

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A novel graphical simulation and animation environment for integrated sensory-motor systems

A novel graphical simulation and animation environment for i...

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IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： S.B. Marapane M.M. Trivedi N. Lassiter Computer Vision Robotics Research Laboratory Electrical Computer Engineering Department University of Tennessee Knoxville TN USA

Describes the status of ongoing work in developing a sensory-motor robotic system, R2H, with 10 degrees of freedoms for research in active vision. To complement the R2H system, a Graphical Simulation and Animation (GSA) environment has also been developed. The objective of building the GSA system is to create a comprehensive design tool to design and study the behavior of active systems and their interactions with the environment. The GSA system will aid the researchers to develop high performance and reliable software and hardware in a most effective manner. The GSA environment integrates sensing and motor actions and features complete kinematic simulation of the R2H system, sensors and its workspace. With the aid of the GSA environment, depth-from-focus, depth-from-vergence, and depth-from-stereo modules have been implemented and tested.

关键词： Animation Robot sensing systems Robot vision systems Buildings Software performance Hardware Kinematics Sensor phenomena and characterization Sensor systems Testing

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