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检索条件"任意字段=Intelligent Robots and Computer Vision XXV: Algorithms, Techniques, and Active Vision"

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Perception system with scene understanding capabilities upon Network-Symbolic models for intelligent tactical behavior of mobile robots in real-world environment

Perception system with scene understanding capabilities upon...

引用

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

作者： Kuvich, Gary Smart Computer Vision Systems

Tactical behavior of UGVs, which is needed for successful autonomous off-road driving, can be in many cases achieved by covering most possible driving situations with a set of rules and switching into a "drive-me-away" semi-autonomous mode when no such rule exists. However, the unpredictable and rapidly changing nature of combat situations requires more intelligent tactical behavior that must be based on predictive situation awareness with ongoing scene understanding and fast autonomous decision making. The implementation of image understanding and active vision is possible in the form of biologically inspired Network-Symbolic models, which combine the power of Computational Intelligence with graph and diagrammatic representation of knowledge. A Network-Symbolic system converts image information into an "understandable" Network-Symbolic format, which is similar to relational knowledge models. The traditional linear bottom-up "segmentation-grouping-learning-recognition" approach cannot provide a reliable separation of an object from its background/clutter, while human vision unambiguously solves this problem. An Image/Video Analysis that is based on Network-Symbolic approach is a combination of recursive hierarchical bottom-up and top-down processes. Logic of visual scenes can be captured in the Network-Symbolic models and used for the reliable disambiguation of visual information, including object detection and identification. Such a system can better interpret images/video for situation awareness, target recognition, navigation and actions and seamlessly integrates into 4D/RCS architecture.

关键词： Mobile robots

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People detection in crowded scenes using active contour models and texture analysis

People detection in crowded scenes using active contour mode...

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

作者： Sidla, Oliver Andreu, Jean P. Paletta, Lucas Lypetskyy, Yuriy JOANNEUM RESEARCH Institute of Digital Image Processing Graz Austria

A vision system designed to detect people in complex backgrounds is presented. The purpose of the proposed algorithms is to allow the identification and tracking of single persons under difficult conditions - in crowded places, under partial occlusion and in low resolution images. In order to detect people reliably, we combine different information channels from video streams. Most emphasis for the initialization of trajectories and the subsequent pedestrian recognition is placed on the detection of the head-shoulder contour. In the first step a simple and fast shape model selects promising candidates, then a local active shape model is matched against the gradients found in the image with the help of a cost function. Texture analysis in the form of co-occurrence features ensures that shape candidates form coherent trajectories over time. In order to reduce the amount of false positives and to become more robust, a pattern analysis step based on Eigenimage analysis is presented. The cues which form the basis of pedestrian detection are integrated into a tracking algorithm which uses the shape information for initial pedestrian detection and verification, propagates positions into new frames using local motion and matches pedestrians with the help of texture information.

关键词： computer vision

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Retinex software or diffractive-optical correlator hardware: The basis of human color vision?

Retinex software or diffractive-optical correlator hardware:...

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

作者： Lauinger, N. CORRSYS-DATRON Sensorsysteme GmbH Wetzlar

Edwin Land - based on photometric data - tried to explain through a retinex (retina + cortex) model calculating scaled integrated reflectances, how human color vision determines the perceived hues of colored Mondrian patches by relating illuminants and 'energies at the eye' and including calculation over the whole image. An alternative - purely optical - model, the diffractive-optical correlator hardware in aperture and image space of the human eye, relating 'local' data onto 'global' data in color vision, becomes illustrated. Based on Edwin Land's experimental data it is shown how the perceived hues result from diffractive-optical transformations and cross-correlations between object space and reciprocal space (RGB space), from matrix multiplications and divisions in vector space. Optical pre-processing causes that our eyes do not see what (physically) is real, but what they optically have calculated. This same diffractive-optical mechanism has also lead to an explanation of the phenomenon of paradoxically colored shadows, shortly re-presented in the introduction.

关键词： computer software

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A simple approach to a vision-guided unmanned vehicle

A simple approach to a vision-guided unmanned vehicle

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

作者： Archibald, Christopher Millar, Evan Anderson, Jon D. Archibald, James K. Lee, Dah-Jye Department of Electrical and Computer Engineering Brigham Young University 459 CB Provo UT 84602

This paper describes the design and implementation of a vision-guided autonomous vehicle that represented BYU in the 2005 intelligent Ground Vehicle Competition (IGVC), in which autonomous vehicles navigate a course marked with white lines while avoiding obstacles consisting of orange construction barrels, white buckets and potholes. Our project began in the context of a senior capstone course in which multi-disciplinary teams of five students were responsible for the design, construction, and programming of their own robots. Each team received a computer motherboard, a camera, and a small budget for the purchase of additional hardware, including a chassis and motors. The resource constraints resulted in a simple vision-based design that processes the sequence of images from the single camera to determine motor controls. Color segmentation separates white and orange from each image, and then the segmented image is examined using a 10×10 grid system, effectively creating a low resolution picture for each of the two colors. Depending on its position, each filled grid square influences the selection of an appropriate turn magnitude. Motor commands determined from the white and orange images are then combined to yield the final motion command for video frame. We describe the complete algorithm and the robot hardware and we present results that show the overall effectiveness of our control approach.

关键词： Unmanned vehicles

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Intersection-point determination in Virtual Keeper using machine vision

Intersection-point determination in Virtual Keeper using mac...

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

作者： Koljonen, Janne Kanniainen, Olli Alander, Jarmo T. Dept. of Electrical Engineering and Industrial Management University of Vaasa Finland

Virtual Keeper is a goalkeeper simulator. It estimates the trajectory of a ball thrown by a player using machine vision and animates a goalkeeper with a video projector. The first version of Virtual Keeper used only one camera. In this paper, a new version that uses two gray-scale cameras for trajectory estimation is proposed. In addition, a color camera and a microphone are used to determine the intersection-point of the ball trajectory and the goal line, in order to enable feedback and online calibration of the machine vision with neural networks, which in turn allows varying external parameters of the cameras and the video projector. The color camera takes images of the goal and determines the positions of the goalposts with pattern matching. After the gray-scale cameras have observed the ball and estimated its trajectory, the sound processing block is triggered. When the ball hits the screen, the noise pattern is recognized with a neural network, whose input consists of temporal and spectral features. The sound processing block in turn triggers the color camera image processing block. The color of the ball differs from the colors of the background and goalkeeper to make the segmentation problem easier. The ball is recognized with fuzzy color based segmentation and fuzzy pattern matching.

关键词： Color image processing

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intelligent mobile robot system for path planning using stereo camera-based geometry information

Intelligent mobile robot system for path planning using ster...

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

作者： Ko, Jung-Hwan Hwang, Dong-Choon Jung, Yong-Woo Kim, Eun-Soo Dept. of Electronic Eng. 3D Display Research Center Kwangwoon University Seoul 139-701 Korea Republic of

In this paper, a new real-time and intelligent mobile robot system for path planning and navigation using stereo camera embedded on the pan/tilt system is proposed. In the proposed system, face area of a moving person is detected from a sequence of the stereo image pairs by using the YCbCr color model and using the disparity map obtained from the left and right images captured by the pan/tilt-controlled stereo camera system and depth information can be detected. And then, the distance between the mobile robot system and the face of the moving person can be calculated from the detected depth information. Accordingly, based-on the analysis of these data, three-dimensional objects can be detected. Finally, by using these detected data, 2-D spatial map for a visually guided robot that can plan paths, navigate surrounding objects and explore an indoor environment is constructed. From some experiments on target tracking with 480 frames of the sequential stereo images, it is analyzed that error ratio between the calculated and measured values of the relative position is found to be very low value of 1.4 % on average. Also, the proposed target tracking system has achieved a high speed of 0.04 sec/frame for target detection and 0.06 sec/frame for target tracking.

关键词： Mobile robots

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Stereo vision-based autonomous mobile robot

Stereo vision-based autonomous mobile robot

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

作者： Park, Changhan Kim, Sooin Paik, Joonki Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University 221 Huksuk-Dong Tongjak-Ku Seoul 156-756 Korea Republic of Department of Internet Information Kimpo College San 14-1 Ponae-Ri Gimpo Gyounggido 415-870 Korea Republic of

In this paper, we propose a method to give more autonomy to a mobile robot by providing vision sensors. The proposed autonomous mobile robot consists of vision, decision, and moving systems. The vision system is based on the stereo technology, which needs correspondence between a set of identical points in the left and the right images. Although mean square difference (MSD) is generally used for the measure of correspondence, it is prone to various types of error caused by: shades, color change, and repetitive texture, to name a few. To correct this error, the four-direction method, which incorporates surrounding information into correspondence measuring, can be used to improve the accuracy of correspondence. Edge of object is first extracted from the Laplacian of Gaussian (LoG) filtered image and post-treatment is performed to eliminate remaining high-frequency noise. During the process to minimize the change of edge, an adaptive threshold value is applied. The extracted edge image is then segmented based on histogram, and it precisely scans candidate blocks for accurate extraction of object. Even if the mobile robot is guaranteed to move autonomously, it has to sublate meaningless movement. To this end, the target is set up for the robot to be able to move toward the designated target and the robot is made to perceive the target by using structural information. The decision system utilizes three-dimensional (3D) distance information extracted from stereo vision and enables dynamic movement to look for a target. Experimental results show average error of 1.25% in the distance estimation, 97% recognition rate of target objects, and 2.3% collision rate with obstacles.

关键词： Mobile robots

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Task-selection and task-merging for directional and vision-based sensors

Task-selection and task-merging for directional and vision-b...

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

作者： Everist, Jacob Nathan Mundhenk, T. Landauer, Chris Bellman, Kirstie University of Southern California Los Angeles CA 90089 Aerospace Corporation 2350 E. El Segundo Blvd El Segundo CA 90245-4691

Many vision research projects involve a sensor or camera doing one thing and doing it well. Fewer research projects have been done involving a sensor trying to satisfy simultaneous and conflicting tasks. Satisfying a task involves pointing the sensor in the direction demanded by the task. We seek ways to mitigate and select between competing tasks and also, if possible, merge the tasks together to be simultaneously achieved by the sensor. This would make a simple pan-tilt camera a very powerful instrument. These two approaches are task-selection and task-merging respectively. We built a simple testbed to implement our task-selection and task-merging schemes. We use a digital camera as our sensor attached to pan and tilt servos capable of pointing the sensor in different directions. We use three different types of tasks for our research: target tracking, surveillance coverage, and initiative. Target tracking is the task of following a target with a known set of features. Surveillance coverage is the task of ensuring that all areas of the space are routinely scanned by the sensor. Initiative is the task of focusing on new things of potential interest should they appear in the course of other activities. Given these heterogeneous task descriptions, we achieve task-selection by assigning priority functions to each task and letting the camera select among the tasks to service. To achieve task-merging, we introduce a concept called "task maps" that represent the regions of space the tasks wish to attend with the sensor. We then merge the task maps and select a region to attend that will satisfy multiple tasks at the same time if possible.

关键词： Image sensors

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The 13th annual intelligent ground vehicle competition: intelligent ground vehicles created by intelligent teams

The 13th annual intelligent ground vehicle competition: Inte...

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

作者： Theisen, Bernard L. U.S. Army Tank Automotive Research Development and Engineering Center 6501 E. Eleven Mile Road Warren MI 48397-5000

The intelligent Ground Vehicle Competition (IGVC) is one of three, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI) in the 1990s. The IGVC is a multidisciplinary exercise in product realization that challenges college engineering student teams to integrate advanced control theory, machine vision, vehicular electronics, and mobile platform fundamentals to design and build an unmanned system. Teams from around the world focus on developing a suite of dual-use technologies to equip ground vehicles of the future with intelligent driving capabilities. Over the past 13 years, the competition has challenged undergraduate, graduate and Ph.D. students with real world applications in intelligent transportation systems, the military and manufacturing automation. To date, teams from over 50 universities and colleges have participated. This paper describes some of the applications of the technologies required by this competition and discusses the educational benefits. The primary goal of the IGVC is to advance engineering education in intelligent vehicles and related technologies. The employment and professional networking opportunities created for students and industrial sponsors through a series of technical events over the three-day competition are highlighted. Finally, an assessment of the competition based on participant feedback is presented.

关键词： intelligent robots

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Software design for an autonomous ground vehicle for the 13th annual intelligent ground vehicle competition

Software design for an autonomous ground vehicle for the 13t...

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

作者： Roberts, Tim Barber, Daniel Becker, Brian C. Gonzalez, Fernando Robotics Laboratory University of Central Florida 3100 Technology Pkwy Orlando FL 32826 United States

This paper presents the vision and path planning software design of a totally autonomous vehicle built to compete in the 13th intelligent Ground Vehicle Competition, IGVC. The vehicle, Calculon, is based on a powered wheelchair and uses a variety of sensors for its navigation and obstacle avoidance including a 3CCD Sony color camera, an outdoor laser range finder, a DGPS, 2 wheel encoders and a solid state compass. The modules forming the core vision system include: filters, color classifier, image segments, and line finder. Our color classifier is based on a modified implementation of an adaptive Gaussian color model similar to those used in some skin detection algorithms. A combination of various image enhancing filters and the color classifier allow for the isolation of possible obstacles within the image. After filtering the image for areas of high brightness and contrast, the line finder performs a Hough Transform to find lines in the image. Our path planning is accomplished using a variety of known and custom algorithms in combination including a modified road map method, a Rapidly Exploring Trees method and a Gaussian Potential Field's method. This paper will present the software design and methods of our autonomous vehicle focusing mainly on the 2 most difficult components, the vision and path planning.

关键词： Ground vehicles

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