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Building Local Safety Maps for a Wheelchair robot using vision and Lasers

Building Local Safety Maps for a Wheelchair Robot using Visi...

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canadian conference on computer and robot vision, crv

作者： A. Murarka J. Modayil B. Kuipers Department of Computer Sciences University of Texas Austin USA

To be useful as a mobility assistant for a human driver, an intelligent robotic wheelchair must be able to distinguish between safe and hazardous regions in its immediate environment. We present a hybrid method using laser rangefinders and vision for building local 2D metrical maps that incorporate safety information (called local safety maps). Laser range-finders are used for localization and mapping of obstacles in the 2D laser plane, and vision is used for detection of hazards and other obstacles in 3D space. The hazards and obstacles identified by vision are projected into the travel plane of the robot and combined with the laser map to construct the local 2D safety map. The main contributions of this work are (i) the definition of a local 2D safety map, (ii) a hybrid method for building the safety map, and (iii) a method for removing noise from dense stereo data using motion.

关键词： Safety Wheelchairs Mobile robots robot vision systems Intelligent robots Hazards Humans Space exploration Orbital robotics Laser noise

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Use of Spatial Reference Systems in Interactive Object Recognition

Use of Spatial Reference Systems in Interactive Object Recog...

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canadian conference on computer and robot vision, crv

作者： R. Kurnia A. Hossain Y. Kuno Saitama University Japan

We are developing a helper robot that carries out tasks ordered by users through speech. The robot needs a vision system to recognize the objects appearing in the orders. It is, however, difficult to realize vision systems that can work in various conditions. They may find many objects and cannot determine which is the target. We have proposed a method of using a conversation with the user to solve this problem. The robot asks questions which the user can easily answer and whose answer can efficiently reduce the number of candidate objects. In our previous system, however, we assumed that there was no occlusion among objects. This paper presents an extended system that can detect target objects in occlusion cases. It is difficult to obtain some features in occlusion cases. To compensate the system for this shortage of features, we propose to use reference systems to express the positional relationships of objects. Experimental results show that the robot can efficiently detect objects through user-friendly conversation.

关键词： Object recognition Machine vision Object detection robot vision systems Speech recognition Layout Aging Medical services Service robots Transient response

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The McGill Object Detection Suite

The McGill Object Detection Suite

引用

canadian conference on computer and robot vision, crv

作者： D.H. Parks M.D. Levine Centre for Intelligent Machines McGill University Montreal QUE Canada

Evaluation of object detection systems requires a set of test images with objects in heterogeneous scenes. Unfortunately, existing publicly available object databases provide few, if any, test images suitable for evaluating object detection systems. Here we present the McGill Object Detection Suite (MODS), a software package for creating test sets suitable for evaluating object detection systems. These test sets are created by superimposing objects from existing publicly available object databases onto heterogeneous backgrounds. The MODS is capable of creating test sets focusing on pose, scale, illumination, occlusion, or noise. This software package is being made publicly available to aid the computer vision community by providing standard test sets which will allow object detection systems to be systematically compared and characterized.

关键词： Object detection Image databases System testing Lighting Software packages Software testing Object recognition Libraries Layout computer vision

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Autonomous Learning of Object Appearances using Colour Contour Frames

Autonomous Learning of Object Appearances using Colour Conto...

引用

canadian conference on computer and robot vision, crv

作者： P. Forssen A. Moe Department of Computer Science Laboratory for Computational Intelligence BC Canada Computer Vision Laboratory Department of Electrical Engineering Linköping University Linkoping Sweden

In this paper we make use of the idea that a robot can autonomously discover objects and learn their appearances by poking and prodding at interesting parts of a scene. In order to make the resultant object recognition ability more robust, and discriminative, we replace earlier used colour histogram features with an invariant texture-patch method. The texture patches are extracted in a similarity invariant frame which is constructed from short colour contour segments. We demonstrate the robustness of our invariant frames with a repeatability test under general homography transformations of a planar scene. Through the repeatability test, we find that defining the frame using using ellipse segments instead of lines where this is appropriate improves repeatability. We also apply the developed features to autonomous learning of object appearances, and show how the learned objects can be recognised under out-of-plane rotation and scale changes.

关键词： Image segmentation computer vision Layout Testing Solid modeling Laboratories robot vision systems Object recognition Robustness Histograms

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Semiautomatic Segmentation with Compact Shapre Prior

Semiautomatic Segmentation with Compact Shapre Prior

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canadian conference on computer and robot vision, crv

作者： P. Das O. Veksler University of Western Ontario London Ontario Vyacheslav Zavadsky Semiconductor Insight Inc. Ottawa Ontario

We present a semiautomatic segmentation algorithm, that can segment an object of interest from its background based on a single user selected seed. We are able to obtain reliable and robust segmentation with such low user interaction by assuming that the object to be segmented is of compact shape (we define this assumption later). We base our work on the powerful Graph Cut segmentation algorithm of Boykov and Jolly [2]. As additional benefit of incorporating the compact shape prior we are able to bias the graph cuts segmentation framework towards larger objects. It helps to counteract the well known bias of [2] to shorter segmentation boundaries. Segmentation results are quite sensitive to the choice of parameters, and so another contribution of our paper is that we show how to select the parameters automatically. We demonstrate the effectiveness of our method on the challenging industrial application of transistor gate segmentation in an integrated chip, for which it produces highly accurate results in realtime.

关键词： computer vision robot vision systems

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Robust Preprocessing Algorithm for Face Recognition

Robust Preprocessing Algorithm for Face Recognition

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canadian conference on computer and robot vision, crv

作者： G. Mittal S. Sasi Computer and Information Science Department Gannon University PA USA

The face recognition includes enhancement and segmentation of face image, detection of face boundary and facial features, matching of extracted features against the features in a database, and finally recognition of the face. The face detection algorithms are based on either gray level template matching or computation of geometric relationships among facial features. Though a number of algorithms are devised for face recognition, the technology is not matured enough to recognize the face of a person with and without beard to be the same. This research proposes a robust algorithm for preprocessing the face image with beard for face recognition. Simulation is done using eighteen JPEG images of 9 different persons having beard and without beard. This research finds application in homeland security where it can increase the robustness of the existing face recognition algorithms.

关键词： Robustness Face recognition Face detection Facial features Image segmentation Feature extraction Image databases Spatial databases Image recognition Terrorism

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A Novel Clustering-Based Method for Adaptive Background Segmentation

A Novel Clustering-Based Method for Adaptive Background Segm...

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canadian conference on computer and robot vision, crv

作者： S. Indupalli M.A. Ali B. Boufama School of Computer Science University of Windsor Windsor Ontario Canada

This paper presents a new histogram-based method for dynamic background modeling using a sequence of images extracted from video. In particular, a k-means clustering technique has been used to identify the foreground objects. Because of its shadow resistance and discriminative properties, we have used images in the HSV color space instead of the traditional RGB color space. The experimental results on real images are very encouraging as we were able to retrieve perfect backgrounds in simple scenes. In very complex scenes, the backgrounds we have obtained were very good. Furthermore, our method is very fast and could be used in real-time applications after optimization.

关键词： Layout Image segmentation Video surveillance Image sequence analysis Video sequences Biomedical monitoring Histograms computer science Vehicle dynamics Immune system

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Tracking 3D free form object in video sequence

Tracking 3D free form object in video sequence

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canadian conference on computer and robot vision, crv

作者： D. Merad J. Didier M. Scuturici LIRIS Laboratory France IBISC Laboratory Evry France

In this paper we describe an original method for the 3D free form object tracking in monocular vision. The main contribution of this article is the use of the skeleton of an object in order to recognize, locate and track this object in real time. Indeed, the use of this kind of representation made it possible to avoid difficulties related to the absence of prominent elements in free form objects (which makes the matching process easier). The skeleton is a lower dimension representation of the object, it is homotopic and it has a graph structure. This allowed us to use powerful tools of the graph theory in order to perform matching between scene objects and models (recognition step). Thereafter, we used skeleton extremities as interest points for the tracking. Keywords: Tracking, 3D free form object, Skeletonization, Graph matching.

关键词： Video sequences Target tracking Skeleton Laboratories Automatic control Image databases Image edge detection Cameras computer vision Image coding

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Detection and tracking of pianist hands and fingers

Detection and tracking of pianist hands and fingers

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canadian conference on computer and robot vision, crv

作者： D.O. Gorodnichy A. Yogeswaran Computational Video Group IIT-ITI NRC-CNRC Computer Engineering Department University of Ottawa Canada

Current MIDI recording and transmitting technology allows teachers to teach piano playing remotely (or off-line): a teacher plays a MIDI-keyboard at one place and a student observes the played piano keys on another MIDI-keyboard at another place. What this technology does not allow is to see how the piano keys are played, namely: which hand and finger was used to play a key. In this paper we present a video recognition tool that makes it possible to provide this information. A video-camera is mounted on top of the piano keyboard and video recognition techniques are then used to calibrate piano image with MIDI sound, then to detect and track pianist hands and then to annotate the fingers that play the piano. The result of the obtained video annotation of piano playing can then be shown on a computer screen for further perusal by a piano teacher or a student.

关键词： Fingers Application software computer vision Video recording Keyboards Image recognition robotics and automation Cameras Virtual colonoscopy Education

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Local Stereo Matching with Segmentation-based Outlier Rejection

Local Stereo Matching with Segmentation-based Outlier Reject...

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canadian conference on computer and robot vision, crv

作者： M. Gerrits P. Bekaert Expertise Centre for Digital Media and transnationale Universiteit Limburg School of Information Technology Hasselt University Diepenbeek Belgium

We present a new window-based stereo matching algorithm which focuses on robust outlier rejection during aggregation. The main difficulty for window-based methods lies in determining the best window shape and size for each pixel. Working from the assumption that depth discontinuities occur at colour boundaries, we segment the reference image and consider all window pixels outside the image segment that contains the pixel under consideration as outliers and greatly reduce their weight in the aggregation process. We developed a variation on the recursive moving average implementation to keep processing times independent from window size. Together with a robust matching cost and the combination of the left and right disparity maps, this gives us a robust local algorithm that approximates the quality of global techniques without sacrificing the speed and simplicity of window-based aggregation.

关键词： Stereo vision Costs Image segmentation Pixel Robustness Shape computer vision Taxonomy Information technology Color

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