Conferences related to Computer Vision

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2014 IEEE 23rd International Symposium on Industrial Electronics (ISIE)

Control Systems & ApplicationsPower ElectronicsSignal Processing & Computational IntelligenceRobotics & MechatronicsSensors, Actuators & System IntegrationElectrical Machines & DrivesFactory Automation & Industrial InformaticsEmerging Technologies

  • 2012 IEEE 21st International Symposium on Industrial Electronics (ISIE)

    IEEE-ISIE is the largest summer conference of the IEEE Industrial Electronics Society, which is an international forum for presentation and discussion of the state of art in Industrial Electronics and related areas.

  • 2011 IEEE 20th International Symposium on Industrial Electronics (ISIE)

    Industrial electronics, power electronics, power converters, electrical machines and drives, signal processing, computational intelligence, mechatronics, robotics, telecommuniction, power systems, renewable energy, factory automation, industrial informatics.

  • 2010 IEEE International Symposium on Industrial Electronics (ISIE 2010)

    Application of electronics and electrical sciences for the enhancement of industrial and manufacturing processes. Latest developments in intelligent and computer control systems, robotics, factory communications and automation, flexible manufacturing, data acquisition and signal processing, vision systems, and power electronics.

  • 2009 IEEE International Symposium on Industrial Electronics (ISIE 2009)

    The purpose of the IEEE international conference is to provide a forum for presentation and discussion of the state-of art of Industrial Electronics and related areas.


2014 IEEE Winter Conference on Applications of Computer Vision (WACV)

Conference Scope: Computer Vision has become increasingly important in real world systems forcommercial, industrial and military applications. Computer Vision related technologies have migrated fromacademic institutions to industrial laboratories, and onward into deployable systems. The goal of thisworkshop is to bring together an international cadre of academic, industrial, and government researchers,along with companies applying vision techniques.

  • 2013 IEEE Workshop on Applications of Computer Vision (WACV)

    Computer Vision has become increasingly important in real world systems for commercial, industrial and military applications. Computer Vision related technologies have migrated from academic institutions to industrial laboratories, and onward into deployable systems. The goal of this workshop is to bring together an international cadre of academic, industrial, and government researchers, along with companies applying vision techniques.

  • 2011 IEEE Workshop on Applications of Computer Vision (WACV)

    Computer Vision has become increasingly important in real world systems for commercial, industrial and military applications. Computer Vision related technologies have started migrating from academic institutions to industrial laboratories, and onward into deployable systems. The goal of this workshop is to bring together an international cadre of academic, industrial, and government researchers, and companies applying vision techniques


IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society

Applications of power electronics, artificial intelligence, robotics, and nanotechnology in electrification of automotive, military, biomedical, and utility industries.

  • IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society

    Industrial and manufacturing theory and applications of electronics, controls, communications, instrumentation and computational intelligence.

  • IECON 2012 - 38th Annual Conference of IEEE Industrial Electronics

    The conference will be focusing on industrial and manufacturing theory and applications of electronics,power, sustainable development, controls, communications, instrumentation and computational intelligence.

  • IECON 2011 - 37th Annual Conference of IEEE Industrial Electronics

    industrial applications of electronics, control, robotics, signal processing, computational and artificial intelligence, sensors and actuators, instrumentation electronics, computer networks, internet and multimedia technologies.

  • IECON 2010 - 36th Annual Conference of IEEE Industrial Electronics

    IECON is an international conference on industrial applications of electronics, control, robotics, signal processing, computational and artificial intelligence, sensors and actuators, instrumentation electronics, computer networks, internet and multimedia technologies. The objectives of the conference are to provide high quality research and professional interactions for the advancement of science, technology, and fellowship.

  • IECON 2009 - 35th Annual Conference of IEEE Industrial Electronics

    Applications of electronics, instrumentation, control and computational intelligence to industrial and manufacturing systems and process. Major themes include power electronics, drives, sensors, actuators, signal processing, motion control, robotics, mechatronics, factory and building automation, and informatics. Emerging technologies and applications such as renewable energy, electronics reuse, and education.


2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)

AVSS focuses on video and signal based surveillance. Topics include: 1) Sensors and data fusion, 2) Processing, detection & recognition, 3) Analytics, behavior & biometrics, 4) Data management and human-computer interfaces, 5) Applications and 6) Privacy Issues


2013 11th International Workshop on Content-Based Multimedia Indexing (CBMI)

The 11th International Content Based Multimedia Indexing Workshop is to bring together the various communities involved in all aspects of content-based multimedia indexing, retrieval, browsing and presentation.The conference will host invited keynote talks and regular, special and demo sessions with contributed research papers.


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Periodicals related to Computer Vision

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Aerospace and Electronic Systems Magazine, IEEE

The IEEE Aerospace and Electronic Systems Magazine publishes articles concerned with the various aspects of systems for space, air, ocean, or ground environments.


Circuits and Systems for Video Technology, IEEE Transactions on

Video A/D and D/A, display technology, image analysis and processing, video signal characterization and representation, video compression techniques and signal processing, multidimensional filters and transforms, analog video signal processing, neural networks for video applications, nonlinear video signal processing, video storage and retrieval, computer vision, packet video, high-speed real-time circuits, VLSI architecture and implementation for video technology, multiprocessor systems--hardware and software-- ...


Information Technology in Biomedicine, IEEE Transactions on

Telemedicine, teleradiology, telepathology, telemonitoring, telediagnostics, 3D animations in health care, health information networks, clinical information systems, virtual reality applications in medicine, broadband technologies, and global information infrastructure design for health care.


Multimedia, IEEE

IEEE Multimedia Magazine covers a broad range of issues in multimedia systems and applications. Articles, product reviews, new product descriptions, book reviews, and announcements of conferences and workshops cover topics that include hardware and software for media compression, coding and processing; media representations and standards for storage, editing, interchange, transmission and presentation; hardware platforms supporting multimedia applications; operating systems suitable ...


Pattern Analysis and Machine Intelligence, IEEE Transactions on

Statistical and structural pattern recognition; image analysis; computational models of vision; computer vision systems; enhancement, restoration, segmentation, feature extraction, shape and texture analysis; applications of pattern analysis in medicine, industry, government, and the arts and sciences; artificial intelligence, knowledge representation, logical and probabilistic inference, learning, speech recognition, character and text recognition, syntactic and semantic processing, understanding natural language, expert systems, ...


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Most published Xplore authors for Computer Vision

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Xplore Articles related to Computer Vision

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Class-Based Matching of Object Parts

E. Bart; S. Ullman 2004 Conference on Computer Vision and Pattern Recognition Workshop, 2004

We develop a novel technique for class-based matching of object parts across large changes in viewing conditions. Given a set of images of objects from a given class under different viewing conditions, the algorithm identifies corresponding regions depicting the same object part in different images. The technique is based on using the equivalence of corresponding features in different viewing conditions. ...


A Mathematical Comparison of Point Detectors

M. Zuliani; C. Kenney; B. S. Manjunath 2004 Conference on Computer Vision and Pattern Recognition Workshop, 2004

Selecting salient points from two or more images for computing correspondences is a fundamental problem in image analysis. Three methods originally proposed by Harris et al. in [A combined corner and edge detector], by Noble et al. in [Descriptions of image surfaces] and by Shi et al. in [Good features to track] proved to be quite effective and robust and ...


Novel Contour Vectorization Using Holistic Feature of Object

Qichao Lu; Guang Yang; Feng Gao 2010 Chinese Conference on Pattern Recognition (CCPR), 2010

In this paper, a novel contour vectorization approach based on holistic feature of object is proposed, which aims at avoiding segmenting an entire contour of target into some discrete sets of curves. This method consists of two steps:(1) Digitize pixel-based contour into vectors or arcs referring to holistic feature of object, and the contour trend used in the implementation of ...


Easy Camera Calibration From Inter-Image Homographies

Xiaochun Cao; H. Foroosh 2004 Conference on Computer Vision and Pattern Recognition Workshop, 2004

This paper addresses the problem of calibrating a pinhole camera using images of a symmetric object. Assuming a unit aspect ratio, and zero skew, we show that inter-image homographies can be expressed as a function of the principal point. By minimizing the symmetric transfer error of geometric distances, we thus obtain an accurate solution for the calibration parameters. We show ...


Texton Finders Based on Gaussian Curvature Of Correlation With An Application To Rapid Texture Classification

S. Ando Proceedings of the 1988 IEEE International Conference on Systems, Man, and Cybernetics, 1988

First Page of the Article ![](/xploreAssets/images/absImages/00754233.png)


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Educational Resources on Computer Vision

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eLearning

Class-Based Matching of Object Parts

E. Bart; S. Ullman 2004 Conference on Computer Vision and Pattern Recognition Workshop, 2004

We develop a novel technique for class-based matching of object parts across large changes in viewing conditions. Given a set of images of objects from a given class under different viewing conditions, the algorithm identifies corresponding regions depicting the same object part in different images. The technique is based on using the equivalence of corresponding features in different viewing conditions. ...


A Mathematical Comparison of Point Detectors

M. Zuliani; C. Kenney; B. S. Manjunath 2004 Conference on Computer Vision and Pattern Recognition Workshop, 2004

Selecting salient points from two or more images for computing correspondences is a fundamental problem in image analysis. Three methods originally proposed by Harris et al. in [A combined corner and edge detector], by Noble et al. in [Descriptions of image surfaces] and by Shi et al. in [Good features to track] proved to be quite effective and robust and ...


Novel Contour Vectorization Using Holistic Feature of Object

Qichao Lu; Guang Yang; Feng Gao 2010 Chinese Conference on Pattern Recognition (CCPR), 2010

In this paper, a novel contour vectorization approach based on holistic feature of object is proposed, which aims at avoiding segmenting an entire contour of target into some discrete sets of curves. This method consists of two steps:(1) Digitize pixel-based contour into vectors or arcs referring to holistic feature of object, and the contour trend used in the implementation of ...


Easy Camera Calibration From Inter-Image Homographies

Xiaochun Cao; H. Foroosh 2004 Conference on Computer Vision and Pattern Recognition Workshop, 2004

This paper addresses the problem of calibrating a pinhole camera using images of a symmetric object. Assuming a unit aspect ratio, and zero skew, we show that inter-image homographies can be expressed as a function of the principal point. By minimizing the symmetric transfer error of geometric distances, we thus obtain an accurate solution for the calibration parameters. We show ...


Texton Finders Based on Gaussian Curvature Of Correlation With An Application To Rapid Texture Classification

S. Ando Proceedings of the 1988 IEEE International Conference on Systems, Man, and Cybernetics, 1988

First Page of the Article ![](/xploreAssets/images/absImages/00754233.png)


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IEEE-USA E-Books

  • Balanced Graph Matching

    Graph matching is a fundamental problem in Computer Vision and Machine Learning. We present two contributions. First, we give a new spectral relaxation technique for approximate solutions to matching problems, that naturally incorporates one-to-one or one-to-many constraints within the relaxation scheme. The second is a normalization procedure for existing graph matching scoring functions that can dramatically improve the matching accuracy. It is based on a reinterpretation of the graph matching compatibility matrix as a bipartite graph on edges for which we seek a bistochastic normalization. We evaluate our two contributions on a comprehensive test set of random graph matching problems, as well as on image correspondence problem. Our normalization procedure can be used to improve the performance of many existing graph matching algorithms, including spectral matching, graduated assignment and semidefinite programming.

  • 2D Shape Measures for Computer Vision

    Shape is a critical element of computer vision systems, and can be used in many ways and for many applications. Examples include classification, partitioning, grouping, registration, data mining, and content based image retrieval. A variety of schemes that compute global shape measures, which can be categorized as techniques based on minimum bounding rectangles, other bounding primitives, fitted shape models, geometric moments, and Fourier descriptors are described.

  • Introduction

    Computer vision is playing an increasingly vital role in three broad areas of intelligent transportation systems: law enforcement, traffic efficiency, and driver safety. This chapter introduces the reader to key applications in each of these domains, whetting the appetite for deeper exploration in subsequent chapters. A basic computer vision pipeline for roadway transportation systems is presented, which serves as an encompassing framework for the techniques presented in the text. The pipeline comprises the modules of image and video acquisition, data preprocessing, feature extraction, inference, and feedback. Each module is summarized in terms of basic concepts, opportunities, and challenges. In addition, a systemic approach is encouraged that exploits interactions among the modules and optimizes the entire pipeline in a holistic manner.

  • No title

    The visual recognition problem is central to computer vision research. From robotics to information retrieval, many desired applications demand the ability to identify and localize categories, places, and objects. This tutorial overviews computer vision algorithms for visual object recognition and image classification. We introduce primary representations and learning approaches, with an emphasis on recent advances in the field. The target audience consists of researchers or students working in AI, robotics, or vision who would like to understand what methods and representations are available for these problems. This lecture summarizes what is and isn't possible to do reliably today, and overviews key concepts that could be employed in systems requiring visual categorization. Table of Contents: Introduction / Overview: Recognition of Specific Objects / Local Features: Detection and Description / Matching Local Features / Geometric Verification of Matched Features / Example Systems: S ecific-Object Recognition / Overview: Recognition of Generic Object Categories / Representations for Object Categories / Generic Object Detection: Finding and Scoring Candidates / Learning Generic Object Category Models / Example Systems: Generic Object Recognition / Other Considerations and Current Challenges / Conclusions

  • The Computational Hoverfly; a Study in Computational Neuroethology

    Studies in computer vision have only recently realised the advantage of adding a behavioural component to vision systems, enabling them to make programmed 'eye movements'. Such an animate vision capability allows the system to employ a nonuniform or foveal sampling strategy, with gaze-control mechanisms repositioning the limited high-resolution area of the visual field. The hoverfly Syritta pipiens is an insect that exhibits foveal animate vision behaviour highly similar to the corresponding activity in humans. This paper discusses a simulation model of Syritta created for studying the neural processes underlying such visually guided behaviour. The approach differs from standard "neural network" modeling techniques in that the simulated Syritta exists within a elosed simulated environment, i.e. there is no need for human intervention: such an approach is an example of computational neuroethology.

  • Recognition and Pose Estimation of Rigid Transparent Objects with a Kinect Sensor

    Recognizing and determining the 6DOF pose of transparent objects is necessary in order for robots to manipulate such objects. However, it is a challenging problem for computer vision. We propose new algorithms for segmentation, pose estimation and recognition of transparent objects from a single RGB-D image from a Kinect sensor. Kinect's weakness in the perception of transparent objects is exploited in their segmentation. Following segmentation, edge fitting is used for recognition and pose estimation. A 3D model of the object is created automatically during training and it is required for pose estimation and recognition. The algorithm is evaluated in different conditions of a domestic environment within the framework of a robotic grasping pipeline where it demonstrates high grasping success rates compared to the state-of- the-art results. The method doesn't deal with occlusions and overlapping transparent objects currently but it is robust against non-transparent clutter.

  • Automated License Plate Recognition

    The ability to recognize and extract license plate information from still images or videos is an essential component of many modern transportation and public safety solutions. Although human review of some imagery is still employed for this purpose, much of this has given way to automated license plate recognition (ALPR). In fact, ALPR has in many ways transformed the public safety and transportation industries¿¿¿helping enable modern tolled roadway solutions, providing tremendous operational cost savings via automation, and even enabling completely new capabilities in the marketplace (e.g., police cruiser¿¿¿mounted license plate reading units). This chapter provides an overview of the technology behind ALPR solutions. The key modules typically found within an ALPR system are outlined, along with highlights of some of the most common methods employed to achieve state¿¿¿of¿¿¿the¿¿¿art performance.

  • No title

    The presence of oriented features in images often conveys important information about the scene or the objects contained; the analysis of oriented patterns is an important task in the general framework of image understanding. As in many other applications of computer vision, the general framework for the understanding of oriented features in images can be divided into low- and high-level analysis. In the context of the study of oriented features, low- level analysis includes the detection of oriented features in images; a measure of the local magnitude and orientation of oriented features over the entire region of analysis in the image is called the orientation field. High- level analysis relates to the discovery of patterns in the orientation field, usually by associating the structure perceived in the orientation field with a geometrical model. This book presents an analysis of several important methods for the detection of oriented features in images, and a discussion of the phase po trait method for high-level analysis of orientation fields. In order to illustrate the concepts developed throughout the book, an application is presented of the phase portrait method to computer-aided detection of architectural distortion in mammograms. Table of Contents: Detection of Oriented Features in Images / Analysis of Oriented Patterns Using Phase Portraits / Optimization Techniques / Detection of Sites of Architectural Distortion in Mammograms

  • Road Condition Monitoring

    Common measurement principles involve in situ measurements, where sensors are embedded in the road surface, and remote sensing technologies using visual cameras and infrared (IR) sensors or cameras. Recent days, development of cooperative traffic systems has increased the expectations concerning automatic road friction measurement units. Automotive industry has been investigating chances to utilize the roadside friction data for adjusting car control functions (i.e., ADAS). This chapter will review the promising camera vision and the short¿¿¿wave IR (SWIR) laser unit technology to provide friction estimation for road users. The laser system consists of two laser diodes emitting at wavelengths ¿¿1¿¿¿=¿¿¿1323¿¿¿nm and ¿¿2¿¿¿=¿¿¿1566¿¿¿nm, whereas the camera system operates in the near¿¿¿IR (NIR) band 850¿¿¿950¿¿¿nm. The algorithms have been developed to identify condition of the road surface (dry, wet, snow, icy, etc.)

  • Appendix A: Order of Operations

    The visual arts are rapidly changing as media moves into the web, mobile devices, and architecture. When designers and artists learn the basics of writing software, they develop a new form of literacy that enables them to create new media for the present, and to imagine future media that are beyond the capacities of current software tools. This book introduces this new literacy by teaching computer programming within the context of the visual arts. It offers a comprehensive reference and text for Processing (www.processing.org), an open-source programming language that can be used by students, artists, designers, architects, researchers, and anyone who wants to program images, animation, and interactivity. Written by Processing's cofounders, the book offers a definitive reference for students and professionals. Tutorial chapters make up the bulk of the book; advanced professional projects from such domains as animation, performance, and installation are discussed in interviews wit their creators. This second edition has been thoroughly updated. It is the first book to offer in-depth coverage of Processing 2.0 and 3.0, and all examples have been updated for the new syntax. Every chapter has been revised, and new chapters introduce new ways to work with data and geometry. New "synthesis" chapters offer discussion and worked examples of such topics as sketching with code, modularity, and algorithms. New interviews have been added that cover a wider range of projects. "Extension" chapters are now offered online so they can be updated to keep pace with technological developments in such fields as computer vision and electronics. **Interviews**SUE.C, Larry Cuba, Mark Hansen, Lynn Hershman Leeson, J??rg Lehni, LettError, Golan Levin and Zachary Lieberman, Benjamin Maus, Manfred Mohr, Ash Nehru, Josh On, Bob Sabiston, Jennifer Steinkamp, Jared Tarbell, Steph Thirion, Robert Winter



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