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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Amodal Completion and Size Constancy in Natural Scenes

Abhishek Kar; Shubham Tulsiani; Joã o Carreira; Jitendra Malik 2015 IEEE International Conference on Computer Vision (ICCV), 2015

We consider the problem of enriching current object detection systems with veridical object sizes and relative depth estimates from a single image. There are several technical challenges to this, such as occlusions, lack of calibration data and the scale ambiguity between object size and distance. These have not been addressed in full generality in previous work. Here we propose to ...


Efficient method for moving object detection in cluttered background using Gaussian Mixture Model

Dileep Kumar Yadav Advances in Computing, Communications and Informatics (ICACCI, 2014 International Conference on, 2014

Foreground object detection in video is a fundamental step for automated video surveillance system and many computer vision applications. Mostly moving foreground object is detected by background subtraction techniques. In dynamic background, Gaussian Mixture Model (GMM) performs better for object detection. In this work, a GMM based Basic Background Subtraction (BBS) model is used for background modeling. The connected component ...


Discrete Tabu Search for Graph Matching

Kamil Adamczewski; Yumin Suh; Kyoung Mu Lee 2015 IEEE International Conference on Computer Vision (ICCV), 2015

Graph matching is a fundamental problem in computer vision. In this paper, we propose a novel graph matching algorithm based on tabu search [13]. The proposed method solves graph matching problem by casting it into an equivalent weighted maximum clique problem of the corresponding association graph, which we further penalize through introducing negative weights. Subsequent tabu search optimization allows for ...


RIDE: Reversal Invariant Descriptor Enhancement

Lingxi Xie; Jingdong Wang; Weiyao Lin; Bo Zhang; Qi Tian 2015 IEEE International Conference on Computer Vision (ICCV), 2015

In many fine-grained object recognition datasets, image orientation (left/right) might vary from sample to sample. Since handcrafted descriptors such as SIFT are not reversal invariant, the stability of image representation based on them is consequently limited. A popular solution is to augment the datasets by adding a left-right reversed copy for each original image. This strategy improves recognition accuracy to ...


Subpixel eye gaze tracking

Jie Zhu; Jie Yang Automatic Face and Gesture Recognition, 2002. Proceedings. Fifth IEEE International Conference on, 2002

This paper addresses the accuracy problem of an eye gaze tracking system. We first analyze the technical barrier for a gaze tracking system to achieve a desired accuracy, and then propose a subpixel tracking method to break this barrier. We present new algorithms for detecting the inner eye corner and the center of an iris at subpixel accuracy, and we ...


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Educational Resources on Computer Vision

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eLearning

Amodal Completion and Size Constancy in Natural Scenes

Abhishek Kar; Shubham Tulsiani; Joã o Carreira; Jitendra Malik 2015 IEEE International Conference on Computer Vision (ICCV), 2015

We consider the problem of enriching current object detection systems with veridical object sizes and relative depth estimates from a single image. There are several technical challenges to this, such as occlusions, lack of calibration data and the scale ambiguity between object size and distance. These have not been addressed in full generality in previous work. Here we propose to ...


Efficient method for moving object detection in cluttered background using Gaussian Mixture Model

Dileep Kumar Yadav Advances in Computing, Communications and Informatics (ICACCI, 2014 International Conference on, 2014

Foreground object detection in video is a fundamental step for automated video surveillance system and many computer vision applications. Mostly moving foreground object is detected by background subtraction techniques. In dynamic background, Gaussian Mixture Model (GMM) performs better for object detection. In this work, a GMM based Basic Background Subtraction (BBS) model is used for background modeling. The connected component ...


Discrete Tabu Search for Graph Matching

Kamil Adamczewski; Yumin Suh; Kyoung Mu Lee 2015 IEEE International Conference on Computer Vision (ICCV), 2015

Graph matching is a fundamental problem in computer vision. In this paper, we propose a novel graph matching algorithm based on tabu search [13]. The proposed method solves graph matching problem by casting it into an equivalent weighted maximum clique problem of the corresponding association graph, which we further penalize through introducing negative weights. Subsequent tabu search optimization allows for ...


RIDE: Reversal Invariant Descriptor Enhancement

Lingxi Xie; Jingdong Wang; Weiyao Lin; Bo Zhang; Qi Tian 2015 IEEE International Conference on Computer Vision (ICCV), 2015

In many fine-grained object recognition datasets, image orientation (left/right) might vary from sample to sample. Since handcrafted descriptors such as SIFT are not reversal invariant, the stability of image representation based on them is consequently limited. A popular solution is to augment the datasets by adding a left-right reversed copy for each original image. This strategy improves recognition accuracy to ...


Subpixel eye gaze tracking

Jie Zhu; Jie Yang Automatic Face and Gesture Recognition, 2002. Proceedings. Fifth IEEE International Conference on, 2002

This paper addresses the accuracy problem of an eye gaze tracking system. We first analyze the technical barrier for a gaze tracking system to achieve a desired accuracy, and then propose a subpixel tracking method to break this barrier. We present new algorithms for detecting the inner eye corner and the center of an iris at subpixel accuracy, and we ...


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IEEE-USA E-Books

  • No title

    As new displays and cameras offer enhanced color capabilities, there is a need to extend the precision of digital content. High Dynamic Range (HDR) imaging encodes images and video with higher than normal 8 bit-per-color-channel precision, enabling representation of the complete color gamut and the full visible range of luminance.However, to realize transition from the traditional toHDRimaging, it is necessary to develop imaging algorithms that work with the high-precision data. Tomake such algorithms effective and feasible in practice, it is necessary to take advantage of the limitations of the human visual system by aligning the data shortcomings to those of the human eye, thus limiting storage and processing precision. Therefore, human visual perception is the key component of the solutions we discuss in this book. This book presents a complete pipeline forHDR image and video processing fromacquisition, through compression and quality evaluation, to display. At the HDR image and vi eo acquisition stage specialized HDR sensors or multi- exposure techniques suitable for traditional cameras are discussed. Then, we present a practical solution for pixel values calibration in terms of photometric or radiometric quantities, which are required in some technically oriented applications. Also, we cover the problem of efficient image and video compression and encoding either for storage or transmission purposes, including the aspect of backward compatibility with existing formats. Finally, we review existing HDR display technologies and the associated problems of image contrast and brightness adjustment. For this purpose tone mapping is employed to accommodate HDR content to LDR devices. Conversely, the so-called inverse tone mapping is required to upgrade LDR content for displaying on HDR devices. We overview HDR-enabled image and video quality metrics, which are needed to verify algorithms at all stages of the pipeline. Additionally, we cover successful examples of the H R technology applications, in particular, in computer graphics and computer vision. The goal of this book is to present all discussed components of the HDR pipeline with the main focus on video. For some pipeline stages HDR video solutions are either not well established or do not exist at all, in which case we describe techniques for single HDR images. In such cases we attempt to select the techniques, which can be extended into temporal domain. Whenever needed, relevant background information on human perception is given, which enables better understanding of the design choices behind the discussed algorithms and HDR equipment. Table of Contents: Introduction / Representation of an HDR Image / HDR Image and Video Acquisition / HDR Image Quality / HDR Image, Video, and Texture Compression / Tone Reproduction / HDR Display Devices / LDR2HDR: Recovering Dynamic Range in Legacy Content / HDRI in Computer Graphics / Software

  • No title

    Malignant tumors due to breast cancer and masses due to benign disease appear in mammograms with different shape characteristics: the former usually have rough, spiculated, or microlobulated contours, whereas the latter commonly have smooth, round, oval, or macrolobulated contours. Features that characterize shape roughness and complexity can assist in distinguishing between malignant tumors and benign masses. In spite of the established importance of shape factors in the analysis of breast tumors and masses, difficulties exist in obtaining accurate and artifact-free boundaries of the related regions from mammograms. Whereas manually drawn contours could contain artifacts related to hand tremor and are subject to intra-observer and inter- observer variations, automatically detected contours could contain noise and inaccuracies due to limitations or errors in the procedures for the detection and segmentation of the related regions. Modeling procedures are desired to eliminate the artifa ts in a given contour, while preserving the important and significant details present in the contour. This book presents polygonal modeling methods that reduce the influence of noise and artifacts while preserving the diagnostically relevant features, in particular the spicules and lobulations in the given contours. In order to facilitate the derivation of features that capture the characteristics of shape roughness of contours of breast masses, methods to derive a signature based on the turning angle function obtained from the polygonal model are described. Methods are also described to derive an index of spiculation, an index characterizing the presence of convex regions, an index characterizing the presence of concave regions, an index of convexity, and a measure of fractal dimension from the turning angle function. Results of testing the methods with a set of 111 contours of 65 benign masses and 46 malignant tumors are presented and discussed. It is shown that shape modeling and a alysis can lead to classification accuracy in discriminating between benign masses and malignant tumors, in terms of the area under the receiver operating characteristic curve, of up to 0.94. The methods have applications in modeling and analysis of the shape of various types of regions or objects in images, computer vision, computer graphics, and analysis of biomedical images, with particular significance in computer-aided diagnosis of breast cancer. Table of Contents: Analysis of Shape / Polygonal Modeling of Contours / Shape Factors for Pattern Classification / Classification of Breast Masses

  • On Forensic Use of Biometrics

    Forensic science largely concerns the analysis of crime. The science of biometrics has developed approaches that are used to automatically identify individuals by personal characteristics. Biometric techniques have primarily been used to assure identity. The main steps of a biometric recognition approach include: acquisition of the biometric data, localization and alignment of the data, feature extraction, and matching. This chapter concentrates on two case studies discussing the forensic possibilities of face and ear as biometrics. It introduces the manual and computer-aided forensic face recognition. The chapter discusses the disparities between the behaviour of the current automatic face recognition systems and that which is needed for forensic application, and outlines the current progress towards addressing the challenges existing in face recognition. An emerging biometric ear is examined. There is a rich variety of approaches for ear biometrics and these are steeped in pattern recognition and computer vision.

  • Topology, Manifolds, Dynamical Systems, Measure, and Bundles

    This chapter contains sections titled: Mathematics as Poetic Material and Material Mode of Articulation, Continuous Topology, Topological Manifolds, Point Set Topology, An Application to Alexander' Patterns, Interlude, An Excursion into the Discrete: Group Algebra, Differential Geometry: Continuous and Differentiable Structures on Topological and Riemannian Manifolds, Ordinary and Partial Differential Equations on Manifolds, Implications and Applications, Computer Vision at the Sony Computer Science Laboratory, The Case for Continua

  • 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

  • Appendix C: Table of Discrete Random Variables and Properties

    An understanding of random processes is crucial to many engineering fields- including communication theory, computer vision, and digital signal processing in electrical and computer engineering, and vibrational theory and stress analysis in mechanical engineering. The filtering, estimation, and detection of random processes in noisy environments are critical tasks necessary in the analysis and design of new communications systems and useful signal processing algorithms. Random Processes: Filtering, Estimation, and Detection clearly explains the basics of probability and random processes and details modern detection and estimation theory to accomplish these tasks. In this book, Lonnie Ludeman, an award-winning authority in digital signal processing, joins the fundamentals of random processes with the standard techniques of linear and nonlinear systems analysis and hypothesis testing to give signal estimation techniques, specify optimum estimation procedures, provide optimum decision rules for classification purposes, and describe performance evaluation definitions and procedures for the resulting methods. The text covers four main, interrelated topics: * Probability and characterizations of random variables and random processes * Linear and nonlinear systems with random excitations * Optimum estimation theory including both the Wiener and Kalman Filters * Detection theory for both discrete and continuous time measurements Lucid, thorough, and well-stocked with numerous examples and practice problems that emphasize the concepts discussed, Random Processes: Filtering, Estimation, and Detection is an understandable and useful text ideal as both a self-study guide for professionals in the field and as a core text for graduate students.

  • No title

    In its early years, the field of computer vision was largely motivated by researchers seeking computational models of biological vision and solutions to practical problems in manufacturing, defense, and medicine. For the past two decades or so, there has been an increasing interest in computer vision as an input modality in the context of human-computer interaction. Such vision-based interaction can endow interactive systems with visual capabilities similar to those important to human-human interaction, in order to perceive non-verbal cues and incorporate this information in applications such as interactive gaming, visualization, art installations, intelligent agent interaction, and various kinds of command and control tasks. Enabling this kind of rich, visual and multimodal interaction requires interactive-time solutions to problems such as detecting and recognizing faces and facial expressions, determining a person's direction of gaze and focus of attention, tracking movement of th body, and recognizing various kinds of gestures. In building technologies for vision-based interaction, there are choices to be made as to the range of possible sensors employed (e.g., single camera, stereo rig, depth camera), the precision and granularity of the desired outputs, the mobility of the solution, usability issues, etc. Practical considerations dictate that there is not a one-size-fits-all solution to the variety of interaction scenarios; however, there are principles and methodological approaches common to a wide range of problems in the domain. While new sensors such as the Microsoft Kinect are having a major influence on the research and practice of vision- based interaction in various settings, they are just a starting point for continued progress in the area. In this book, we discuss the landscape of history, opportunities, and challenges in this area of vision-based interaction; we review the state-of-the-art and seminal works in detecting and recognizing the human b dy and its components; we explore both static and dynamic approaches to "looking at people" vision problems; and we place the computer vision work in the context of other modalities and multimodal applications. Readers should gain a thorough understanding of current and future possibilities of computer vision technologies in the context of human- computer interaction.

  • No title

    <p>Because circular objects are projected to ellipses in images, ellipse fitting is a first step for 3-D analysis of circular objects in computer vision applications. For this reason, the study of ellipse fitting began as soon as computers came into use for image analysis in the 1970s, but it is only recently that optimal computation techniques based on the statistical properties of noise were established. These include renormalization (1993), which was then improved as FNS (2000) and HEIV (2000). Later, further improvements, called hyperaccurate correction (2006), HyperLS (2009), and hyper-renormalization (2012), were presented. Today, these are regarded as the most accurate fitting methods among all known techniques. This book describes these algorithms as well implementation details and applications to 3-D scene analysis. </p><p> We also present general mathematical theories of statistical optimization underlying all ellipse fitting algorithms, including rig rous covariance and bias analyses and the theoretical accuracy limit. The results can be directly applied to other computer vision tasks including computing fundamental matrices and homographies between images. </p><p> This book can serve not simply as a reference of ellipse fitting algorithms for researchers, but also as learning material for beginners who want to start computer vision research. The sample program codes are downloadable from the website: https://sites.google.com/a/morganclaypool.com/ellipse-fitting-for-computer- vision-implementation-and-applications.</p>

  • Back Matter

    Mobile robots range from the Mars Pathfinder mission's teleoperated Sojourner to the cleaning robots in the Paris Metro. This text offers students and other interested readers an introduction to the fundamentals of mobile robotics, spanning the mechanical, motor, sensory, perceptual, and cognitive layers the field comprises. The text focuses on mobility itself, offering an overview of the mechanisms that allow a mobile robot to move through a real world environment to perform its tasks, including locomotion, sensing, localization, and motion planning. It synthesizes material from such fields as kinematics, control theory, signal analysis, computer vision, information theory, artificial intelligence, and probability theory. The book presents the techniques and technology that enable mobility in a series of interacting modules. Each chapter treats a different aspect of mobility, as the book moves from low-level to high-level details. It covers all aspects of mobile robotics, including software and hardware design considerations, related technologies, and algorithmic techniques.] This second edition has been revised and updated throughout, with 130 pages of new material on such topics as locomotion, perception, localization, and planning and navigation. Problem sets have been added at the end of each chapter. Bringing together all aspects of mobile robotics into one volume, Introduction to Autonomous Mobile Robots can serve as a textbook or a working tool for beginning practitioners.

  • 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.



Standards related to Computer Vision

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No standards are currently tagged "Computer Vision"