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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Some Discussion on the Conditions of the Unique Solution of P3P Problem

Wang Ting; Wang Yuecao; Yao Chen 2006 International Conference on Mechatronics and Automation, 2006

The multi-solution phenomenon of P3P problem limits its applications in practices. In some specific case, if we know the relative pose between control points and camera in advance, then it is likely to get the unique solution of P3P problem easily. Combined with predecessor's work, this paper presents a much more integrated analysis of the unique solution region of specific ...


Towards multiple-orientation based tensor invariants for object tracking

Nicolaj C. Stache; Thomas H. Stehle; Matthias Mühlich; Til Aach 2006 14th European Signal Processing Conference, 2006

We derive a new scale- and rotation-invariant feature for characterizing local neighbourhoods in images, which is applicable in tasks such as tracking. Our approach is motivated by the estimation of optical flow. Its least-squares estimate requires the inversion of a symmetric and positive semi-definite 2×2-tensor, which is computed from spatial image derivatives. Only if one eigenvalue of the tensor vanishes, ...


An accurate and automatic color correction method for digital films based on a physical model

Quoc Bao Do; Azeddine Beghdadi; Marie Luong 2011 19th European Signal Processing Conference, 2011

A new method for detecting and correcting color-mismatch in digital film is proposed. This method is based on a physical model which accounts for the absorption of light by the different layers of the film. The whole process consists of three sequential stages. Based on the physical model, a robust optical flow method which is invariant to color change is ...


Demo: An embedded vision system for high frame rate visual servoing

Zhenyu Ye; Yifan He; Roel Pieters; Bart Mesman; Henk Corporaal; Pieter Jonker 2011 Fifth ACM/IEEE International Conference on Distributed Smart Cameras, 2011

The frame rate of commercial off-the-shelf industrial cameras is breaking the threshold of 1000 frames-per-second, the sample rate required in high performance motion control systems. On the one hand, it enables computer vision as a cost-effective feedback source; On the other hand, it imposes multiple challenges on the vision processing system. The authors have designed and implemented an FPGA-based embedded ...


Site model acquisition and extension from aerial images

R. T. Collins; Yong-Qing Cheng; C. Jaynes; F. Stolle; Xiaoguang Wang; A. R. Hanson; E. M. Riseman Proceedings of IEEE International Conference on Computer Vision, 1995

A system has been developed to acquire, extend and refine 3D geometric site models from aerial imagery. This system hypothesizes potential building roofs in an image, automatically locates supporting geometric evidence in other images, and determines the precise shape and position of the new buildings via multiimage triangulation. Model-to-image registration techniques are applied to align new, incoming images against the ...


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Educational Resources on Computer Vision

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eLearning

Some Discussion on the Conditions of the Unique Solution of P3P Problem

Wang Ting; Wang Yuecao; Yao Chen 2006 International Conference on Mechatronics and Automation, 2006

The multi-solution phenomenon of P3P problem limits its applications in practices. In some specific case, if we know the relative pose between control points and camera in advance, then it is likely to get the unique solution of P3P problem easily. Combined with predecessor's work, this paper presents a much more integrated analysis of the unique solution region of specific ...


Towards multiple-orientation based tensor invariants for object tracking

Nicolaj C. Stache; Thomas H. Stehle; Matthias Mühlich; Til Aach 2006 14th European Signal Processing Conference, 2006

We derive a new scale- and rotation-invariant feature for characterizing local neighbourhoods in images, which is applicable in tasks such as tracking. Our approach is motivated by the estimation of optical flow. Its least-squares estimate requires the inversion of a symmetric and positive semi-definite 2×2-tensor, which is computed from spatial image derivatives. Only if one eigenvalue of the tensor vanishes, ...


An accurate and automatic color correction method for digital films based on a physical model

Quoc Bao Do; Azeddine Beghdadi; Marie Luong 2011 19th European Signal Processing Conference, 2011

A new method for detecting and correcting color-mismatch in digital film is proposed. This method is based on a physical model which accounts for the absorption of light by the different layers of the film. The whole process consists of three sequential stages. Based on the physical model, a robust optical flow method which is invariant to color change is ...


Demo: An embedded vision system for high frame rate visual servoing

Zhenyu Ye; Yifan He; Roel Pieters; Bart Mesman; Henk Corporaal; Pieter Jonker 2011 Fifth ACM/IEEE International Conference on Distributed Smart Cameras, 2011

The frame rate of commercial off-the-shelf industrial cameras is breaking the threshold of 1000 frames-per-second, the sample rate required in high performance motion control systems. On the one hand, it enables computer vision as a cost-effective feedback source; On the other hand, it imposes multiple challenges on the vision processing system. The authors have designed and implemented an FPGA-based embedded ...


Site model acquisition and extension from aerial images

R. T. Collins; Yong-Qing Cheng; C. Jaynes; F. Stolle; Xiaoguang Wang; A. R. Hanson; E. M. Riseman Proceedings of IEEE International Conference on Computer Vision, 1995

A system has been developed to acquire, extend and refine 3D geometric site models from aerial imagery. This system hypothesizes potential building roofs in an image, automatically locates supporting geometric evidence in other images, and determines the precise shape and position of the new buildings via multiimage triangulation. Model-to-image registration techniques are applied to align new, incoming images against the ...


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IEEE-USA E-Books

  • No title

    Image understanding has been playing an increasingly crucial role in several inverse problems and computer vision. Sparse models form an important component in image understanding, since they emulate the activity of neural receptors in the primary visual cortex of the human brain. Sparse methods have been utilized in several learning problems because of their ability to provide parsimonious, interpretable, and efficient models. Exploiting the sparsity of natural signals has led to advances in several application areas including image compression, denoising, inpainting, compressed sensing, blind source separation, super-resolution, and classification. The primary goal of this book is to present the theory and algorithmic considerations in using sparse models for image understanding and computer vision applications. To this end, algorithms for obtaining sparse representations and their performance guarantees are discussed in the initial chapters. Furthermore, approaches for designing ov rcomplete, data-adapted dictionaries to model natural images are described. The development of theory behind dictionary learning involves exploring its connection to unsupervised clustering and analyzing its generalization characteristics using principles from statistical learning theory. An exciting application area that has benefited extensively from the theory of sparse representations is compressed sensing of image and video data. Theory and algorithms pertinent to measurement design, recovery, and model-based compressed sensing are presented. The paradigm of sparse models, when suitably integrated with powerful machine learning frameworks, can lead to advances in computer vision applications such as object recognition, clustering, segmentation, and activity recognition. Frameworks that enhance the performance of sparse models in such applications by imposing constraints based on the prior discriminatory information and the underlying geometrical structure, and kernelizing the spa se coding and dictionary learning methods are presented. In addition to presenting theoretical fundamentals in sparse learning, this book provides a platform for interested readers to explore the vastly growing application domains of sparse representations.

  • Intersection Monitoring Using Computer Vision Techniques for Capacity, Delay, and Safety Analysis

    In this chapter, intersection analysis including capacity, delay, and safety is presented using computer vision techniques. An intersection appropriate vision???based tracking system is presented, which aims to provide long???term tracks of road users provide classification (i.e., vehicle and pedestrian) and handle the partial occlusion problem. Road trajectories are further investigated and modeled to provide road user count, vehicle queue length, and safety analysis including accidents and conflicts. Since accidents are infrequent events, surrogate safety measurements were leveraged to provide conflict severity measures at intersection facilities. Finally, technology???enhanced safety for all participants, including vehicles, drivers, and pedestrians, through communication and sharing of dynamic profiles between infrastructure and cooperative vehicles is highlighted.

  • Code Index

    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

  • Video???Based Parking Management

    This chapter examines the state of the art in visual parking space monitoring. Available methods for occupancy detection are presented, beginning with two???dimensional (2D) methods. Vehicle detectors which are based on background modeling, feature detection, and more specific appearance???based histogram of oriented gradient (HOG) and HOG/local binary pattern (LBP) detectors are analyzed. The second part of the chapter treats 3D methods for parking space monitoring and focuses mainly on stereoscopic imaging. It includes the detailed analysis of a state???of???the???art 3D stereo system system.

  • Index

    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

  • Environmental Informatics for Integrated Solid Waste Management

    Environmental informatics is a highly interdisciplinary science, where synergistic efforts among environmental sciences, electronic engineering, and computer sciences can be signified and magnified in regard to data collection, data analysis, data evaluation, and data visualization using specific computational intelligence methodologies, networking and sensing, cyber infrastructure platforms, virtual reality and computer vision, and data science tools for solving environmental problems. This chapter focuses on the major categories of the environmental informatics methods and tools applied in integrated solid waste management (ISWM), from data collection through sensors and sensor networks, to data management through database design, and to data evaluation and assessment through geographical information systems (GIS), global positioning systems (GPS) and associated spatial analysis methods.

  • Applications: Learning

    Regression and classification methods based on similarity of the input to stored examples have not been widely used in applications involving very large sets of high-dimensional data. Recent advances in computational geometry and machine learning, however, may alleviate the problems in using these methods on large data sets. This volume presents theoretical and practical discussions of nearest-neighbor (NN) methods in machine learning and examines computer vision as an application domain in which the benefit of these advanced methods is often dramatic. It brings together contributions from researchers in theory of computation, machine learning, and computer vision with the goals of bridging the gaps between disciplines and presenting state-of-the-art methods for emerging applications.The contributors focus on the importance of designing algorithms for NN search, and for the related classification, regression, and retrieval tasks, that remain efficient even as the number of points or the dimensionality of the data grows very large. The book begins with two theoretical chapters on computational geometry and then explores ways to make the NN approach practicable in machine learning applications where the dimensionality of the data and the size of the data sets make the naïve methods for NN search prohibitively expensive. The final chapters describe successful applications of an NN algorithm, locality-sensitive hashing (LSH), to vision tasks.

  • Video Anomaly Detection

    We present a comprehensive overview of techniques for detecting rare or unusual patterns in transportation video. The anomaly detection problem is parsed into two stages: event encoding and anomaly detection model, and various approaches in each stage are presented. Anomaly detection models are broadly classified into structured versus unstructured and supervised versus unsupervised methods, based on how much information is known about normal and anomalous events during training. Spanning these categories, four flavors of models are presented: classification methods, hidden Markov models, contextual techniques, and sparsity models. As a recent promising approach in this domain, the sparsity model is presented in significant detail along with experimental results. The chapter ends with open problems and future research directions in the area.

  • Sensorimotor transformations in the worlds of frogs and robots

    The paper develops a multilevel approach to the design and analysis of systems with "action-oriented perception", situating various robot and animal "designs" in an evolutionary perspective. We present a set of biological design principles within a broader perspective that shows their relevance for robot design. We introduce schemas to provide a coarse-grain analysis of "cooperative computation" in the brains of animals and the "brains" of robots, starting with an analysis of approach, avoidance, detour behavior, and path planning in frogs. An explicit account of neural mechanism of avoidance behavior in the frog illustrates how schemas may be implemented in neural networks. The focus of the rest of the article is on the relation of instinctive to reflective behavior. We generalize an analysis of the interaction of perceptual schemas in the VISIONS system for computer vision to a view of the interaction of perceptual and motor schemas in distributed planning which, we argue, has great promise for integrating mechanisms for action and perception in both animal and robot. We conclude with general observations on the lessons on relating structure and function which can be carried from biology to technology.

  • No title

    Light field is one of the most representative image-based rendering techniques that generate novel virtual views from images instead of 3D models. The light field capture and rendering process can be considered as a procedure of sampling the light rays in the space and interpolating those in novel views. As a result, light field can be studied as a high-dimensional signal sampling problem, which has attracted a lot of research interest and become a convergence point between computer graphics and signal processing, and even computer vision. This lecture focuses on answering two questions regarding light field sampling, namely how many images are needed for a light field, and if such number is limited, where we should capture them. The book can be divided into three parts. First, we give a complete analysis on uniform sampling of IBR data. By introducing the surface plenoptic function, we are able to analyze the Fourier spectrum of non-Lambertian and occluded scenes. Given the spectrum, we also apply the generalized sampling theorem on the IBR data, which results in better rendering quality than rectangular sampling for complex scenes. Such uniform sampling analysis provides general guidelines on how the images in IBR should be taken. For instance, it shows that non- Lambertian and occluded scenes often require a higher sampling rate. Next, we describe a very general sampling framework named freeform sampling. Freeform sampling handles three kinds of problems: sample reduction, minimum sampling rate to meet an error requirement, and minimization of reconstruction error given a fixed number of samples. When the to-be-reconstructed function values are unknown, freeform sampling becomes active sampling. Algorithms of active sampling are developed for light field and show better results than the traditional uniform sampling approach. Third, we present a self-reconfigurable camera array that we developed, which features a very efficient algorithm for real-time rendering an the ability of automatically reconfiguring the cameras to improve the rendering quality. Both are based on active sampling. Our camera array is able to render dynamic scenes interactively at high quality. To the best of our knowledge, it is the first camera array that can reconfigure the camera positions automatically.



Standards related to Computer Vision

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No standards are currently tagged "Computer Vision"