Download or read book Scene Reconstruction Pose Estimation and Tracking written by Rustam Stolkin and published by BoD – Books on Demand. This book was released on 2007-06-01 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reports recent advances in the use of pattern recognition techniques for computer and robot vision. The sciences of pattern recognition and computational vision have been inextricably intertwined since their early days, some four decades ago with the emergence of fast digital computing. All computer vision techniques could be regarded as a form of pattern recognition, in the broadest sense of the term. Conversely, if one looks through the contents of a typical international pattern recognition conference proceedings, it appears that the large majority (perhaps 70-80%) of all pattern recognition papers are concerned with the analysis of images. In particular, these sciences overlap in areas of low level vision such as segmentation, edge detection and other kinds of feature extraction and region identification, which are the focus of this book.

Download or read book Scene Reconstruction Pose Estimation and Tracking written by Rustam Stolkin and published by IntechOpen. This book was released on 2007-06-01 with total page 542 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reports recent advances in the use of pattern recognition techniques for computer and robot vision. The sciences of pattern recognition and computational vision have been inextricably intertwined since their early days, some four decades ago with the emergence of fast digital computing. All computer vision techniques could be regarded as a form of pattern recognition, in the broadest sense of the term. Conversely, if one looks through the contents of a typical international pattern recognition conference proceedings, it appears that the large majority (perhaps 70-80%) of all pattern recognition papers are concerned with the analysis of images. In particular, these sciences overlap in areas of low level vision such as segmentation, edge detection and other kinds of feature extraction and region identification, which are the focus of this book.

Download or read book Visual Inertial Odometry for 3D Pose Estimation and Scene Reconstruction Using Unmanned Aerial Vehicles written by Dylan Gareau and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: As Unmanned Aerial Vehicles (UAVs) become increasingly available, pose estimation remains critical for navigation. Pose estimation is also useful for scene reconstruction in certain surveillance applications, such as surveillance in the event of a natural disaster. This thesis presents a Direct Sparse Visual-Inertial Odometry with Loop Closure (VIL-DSO) algorithm design as a pose estimation solution, combining several existing algorithms to fuse inertial and visual information to improve pose estimation and provide metric scale, as initially implemented in Direct Sparse Odometry (DSO) and Direct Sparse Visual-Inertial Odometry (VI-DSO). VIL-DSO utilizes the point selection and loop closure method of the Direct Sparse Odometry with Loop Closure (LDSO) approach. This point selection method improves repeatability by calculating the Shi-Tomasi score to favor corners as point candidates and allows for generating matches for loop closure between keyframes. The proposed VIL-DSO then uses the Kabsch-Umeyama algorithm to reduce the effects of scale-drift caused by loop closure. The proposed VIL-DSO algorithm is composed of three main threads for computing: a coarse tracking thread to assist with keyframe selection and initial pose estimation, a local window optimization thread to fuse Inertial Measurement Unit (IMU) information and visual information to pose scale and pose estimate, and a global optimization thread to identify loop closure and improve pose estimates. The loop closure thread also includes the modification to mitigate scale-drift using the Kabsch-Umeyama algorithm. The trajectory analysis of the estimates yields that the loop closure improves the pose estimation, but causes to scale estimate to drift. The scale-drift mitigation method successfully improves the scale estimate after loop closure. However, the estimation error level struggles to exceed the other state-of-the-art methods, namely VI-DSO and VI-ORB SLAM. The results were evaluated on the EuRoC MAV dataset, which contains fairly short sequences. VIL-DSO is expected to show more advantages when used on a longer dataset,where loop closure is more useful. Lastly, using the odometry as a feed, scene reconstruction and the effects of various factors regarding mapping are discussed, including the use of a monocular camera, camera angle and resolution in outdoor settings.

Download or read book 3D Computer Vision written by Christian Wöhler and published by Springer Science & Business Media. This book was released on 2012-07-23 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: This indispensable text introduces the foundations of three-dimensional computer vision and describes recent contributions to the field. Fully revised and updated, this much-anticipated new edition reviews a range of triangulation-based methods, including linear and bundle adjustment based approaches to scene reconstruction and camera calibration, stereo vision, point cloud segmentation, and pose estimation of rigid, articulated, and flexible objects. Also covered are intensity-based techniques that evaluate the pixel grey values in the image to infer three-dimensional scene structure, and point spread function based approaches that exploit the effect of the optical system. The text shows how methods which integrate these concepts are able to increase reconstruction accuracy and robustness, describing applications in industrial quality inspection and metrology, human-robot interaction, and remote sensing.

Download or read book Robust Video Object Tracking Via Camera Self calibration written by Zheng Tang and published by . This book was released on 2019 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, a framework for 3D scene reconstruction based on robust video object tracking assisted by camera self-calibration is proposed, which includes several algorithmic components. (1) An algorithm for joint camera self-calibration and automatic radial distortion correction based on tracking of walking persons is designed to convert multiple object tracking into 3D space. (2) An adaptive model that learns online a relatively long-term appearance change of each target is proposed for robust 3D tracking. (3) We also develop an iterative two-step evolutionary optimization scheme to estimate 3D pose of each human target, which can jointly compute the camera trajectory for a moving camera as well. (4) With 3D tracking results and human pose information from multiple views, we propose multi-view 3D scene reconstruction based on data association with visual and semantic attributes. Camera calibration and radial distortion correction are crucial prerequisites for 3D scene understanding. Many existing works rely on the Manhattan world assumption to estimate camera parameters automatically, however, they may perform poorly when lack of man-made structure in the scene. As walking humans are common objects in video analytics, they have also been used for camera calibration, but the main challenges include noise reduction for the estimation of vanishing points, the relaxation of assumptions on unknown camera parameters, and radial distortion correction. We propose a novel framework for camera self-calibration and automatic radial distortion correction. Our approach starts with a multi-kernel-based adaptive segmentation and tracking scheme that dynamically controls the decision thresholds of background subtraction and shadow removal around the adaptive kernel regions based on the preliminary tracking results. With the head/foot points collected from tracking and segmentation results, mean shift clustering and Laplace linear regression are introduced in the estimation of the vertical vanishing point and the horizon line, respectively. The estimation of distribution algorithm (EDA), an evolutionary optimization scheme, is then utilized to optimize the camera parameters and distortion coefficients, in which all the unknowns in camera projection can be fine-tuned simultaneously. Experiments on three public benchmarks and our own captured dataset demonstrate the robustness of the proposed method. The superiority of this algorithm is also verified by the capability of reliably converting 2D object tracking into 3D space. Multiple object tracking has been a challenging field, mainly due to noisy detection sets and identity switch caused by occlusion and similar appearance among nearby targets. Previous works rely on appearance models built on individual or several selected frames for the comparison of features, but they cannot encode long-term appearance change caused by pose, viewing angle and lighting condition. We propose an adaptive model that learns online a relatively long-term appearance change of each target. The proposed model is compatible with any features of fixed dimension or their combinations, whose learning rates are dynamically controlled by adaptive update and spatial weighting schemes. To handle occlusion and nearby objects sharing similar appearance, we also design cross-matching and re-identification schemes based on the proposed adaptive appearance models. Additionally, the 3D geometry information is effectively incorporated in our formulation for data association. The proposed method outperforms all the state-of-the-art on the MOTChallenge 3D benchmark and achieves real-time computation with only a standard desktop CPU. It has also shown superior performance over the state-of-the-art on the 2D benchmark of MOTChallenge. For more comprehensive 3D scene reconstruction, we develop a monocular 3D human pose estimation algorithm based on two-step EDA that can simultaneously estimate the camera motion for a moving camera. We first derive reliable 2D joint points through deep-learning-based 2D pose estimation and feature tracking. If the camera is moving, the initial camera poses can be estimated from visual odometry, where the feature points extracted on the human bodies are removed by segmentation masks dilated from 2D skeletons. Then the 3D joint points and camera parameters are iteratively optimized through a two-step evolutionary algorithm. The cost function for human pose optimization consists of loss terms defined by spatial and temporal constancy, "flatness" of human bodies, and joint angle constraints. On the other hand, the optimization for camera movement is based on the minimization of reprojection error of skeleton joint points. Extensive experiments have been conducted on various video data, which verify the robustness of the proposed method. The final goal of our work is to fully understand and reconstruct the 3D scene, i.e., to recover the trajectory and action of each object. The above methods can be extended to a system with camera array of overlapping views. We propose a novel video scene reconstruction framework to collaboratively track multiple human objects and estimate their 3D poses across multiple camera views. First, tracklets are extracted from each single view following the tracking-by-detection paradigm. We propose an effective integration of visual and semantic object attributes, including appearance models, geometry information and poses/actions, to associate tracklets across different views. Based on the optimum viewing perspectives derived from tracking, we generate the 3D skeleton of each object. The estimated body joint points are fed back to the tracking stage to enhance tracklet association. Experiments on a benchmark of multi-view tracking validate our effectiveness.

Download or read book On Pose Estimation in Room Scaled Environments written by Hanna E. Nyqvist and published by Linköping University Electronic Press. This book was released on 2016-11-22 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pose (position and orientation) tracking in room-scaled environments is an enabling technique for many applications. Today, virtual reality (vr) and augmented reality (ar) are two examples of such applications, receiving high interest both from the public and the research community. Accurate pose tracking of the vr or ar equipment, often a camera or a headset, or of different body parts is crucial to trick the human brain and make the virtual experience realistic. Pose tracking in room-scaled environments is also needed for reference tracking and metrology. This thesis focuses on an application to metrology. In this application, photometric models of a photo studio are needed to perform realistic scene reconstruction and image synthesis. Pose tracking of a dedicated sensor enables creation of these photometric models. The demands on the tracking system used in this application is high. It must be able to provide sub-centimeter and sub-degree accuracy and at same time be easy to move and install in new photo studios. The focus of this thesis is to investigate and develop methods for a pose tracking system that satisfies the requirements of the intended metrology application. The Bayesian filtering framework is suggested because of its firm theoretical foundation in informatics and because it enables straightforward fusion of measurements from several sensors. Sensor fusion is in this thesis seen as a way to exploit complementary characteristics of different sensors to increase tracking accuracy and robustness. Four different types of measurements are considered; inertialmeasurements, images from a camera, range (time-of-flight) measurements from ultra wide band (uwb) radio signals, and range and velocity measurements from echoes of transmitted acoustic signals. A simulation study and a study of the Cramér-Rao lower filtering bound (crlb) show that an inertial-camera system has the potential to reach the required tracking accuracy. It is however assumed that known fiducial markers, that can be detected and recognized in images, are deployed in the environment. The study shows that many markers are required. This makes the solution more of a stationary solution and the mobility requirement is not fulfilled. A simultaneous localization and mapping (slam) solution, where naturally occurring features are used instead of known markers, are suggested solve this problem. Evaluation using real data shows that the provided inertial-camera slam filter suffers from drift but that support from uwb range measurements eliminates this drift. The slam solution is then only dependent on knowing the position of very few stationary uwb transmitters compared to a large number of known fiducial markers. As a last step, to increase the accuracy of the slam filter, it is investigated if and how range measurements can be complemented with velocity measurement obtained as a result of the Doppler effect. Especially, focus is put on analyzing the correlation between the range and velocity measurements and the implications this correlation has for filtering. The investigation is done in a theoretical study of reflected known signals (compare with radar and sonar) where the crlb is used as an analyzing tool. The theory is validated on real data from acoustic echoes in an indoor environment.

Download or read book Scene Reconstruction Pose Estimation and Tracking written by Rustam Stolkin and published by IntechOpen. This book was released on 2007-06-01 with total page 542 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reports recent advances in the use of pattern recognition techniques for computer and robot vision. The sciences of pattern recognition and computational vision have been inextricably intertwined since their early days, some four decades ago with the emergence of fast digital computing. All computer vision techniques could be regarded as a form of pattern recognition, in the broadest sense of the term. Conversely, if one looks through the contents of a typical international pattern recognition conference proceedings, it appears that the large majority (perhaps 70-80%) of all pattern recognition papers are concerned with the analysis of images. In particular, these sciences overlap in areas of low level vision such as segmentation, edge detection and other kinds of feature extraction and region identification, which are the focus of this book.

Download or read book Multimodal Analytics for Next Generation Big Data Technologies and Applications written by Kah Phooi Seng and published by Springer. This book was released on 2019-07-18 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited book will serve as a source of reference for technologies and applications for multimodality data analytics in big data environments. After an introduction, the editors organize the book into four main parts on sentiment, affect and emotion analytics for big multimodal data; unsupervised learning strategies for big multimodal data; supervised learning strategies for big multimodal data; and multimodal big data processing and applications. The book will be of value to researchers, professionals and students in engineering and computer science, particularly those engaged with image and speech processing, multimodal information processing, data science, and artificial intelligence.

Download or read book Multimedia Communications Services and Security written by Andrzej Dziech and published by Springer. This book was released on 2013-05-16 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the refereed proceedings of the 6th International Conference on Multimedia Communications, Services and Security, MCSS 2013, held in Krakow, Poland, in June 2013. The 27 full papers included in the volume were selected from numerous submissions. The papers cover various topics related to multimedia technology and its application to public safety problems.

Download or read book Computer Vision written by Li Fei-Fei and published by Morgan & Claypool. This book was released on 2013-02-01 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: When a 3-dimensional world is projected onto a 2-dimensional image, such as the human retina or a photograph, reconstructing back the layout and contents of the real-world becomes an ill-posed problem that is extremely difficult to solve. Humans possess the remarkable ability to navigate and understand the visual world by solving the inversion problem going from 2D to 3D. Computer Vision seeks to imitate such abilities of humans to recognize objects, navigate scenes, reconstruct layouts, and understand the geometric space and semantic meaning of the visual world. These abilities are critical in many applications including robotics, autonomous driving and exploration, photo organization, image, or video retrieval, and human-computer interaction. This book delivers a systematic overview of computer vision, comparable to that presented in an advanced graduate level class. The authors emphasize two key issues in modeling vision: space and meaning, and focus upon the main problems vision needs to solve, including: * mapping out the 3D structure of objects and scenes* recognizing objects* segmenting objects* recognizing meaning of scenes* understanding movements of humansMotivated by these important problems and centered on the understanding of space and meaning, the book explores the fundamental theories and important algorithms of computer vision, starting from the analysis of 2D images, and culminating in the holistic understanding of a 3D scene

Download or read book Image Processing and Analysis with Graphs written by Olivier Lezoray and published by CRC Press. This book was released on 2017-07-12 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covering the theoretical aspects of image processing and analysis through the use of graphs in the representation and analysis of objects, Image Processing and Analysis with Graphs: Theory and Practice also demonstrates how these concepts are indispensible for the design of cutting-edge solutions for real-world applications. Explores new applications in computational photography, image and video processing, computer graphics, recognition, medical and biomedical imaging With the explosive growth in image production, in everything from digital photographs to medical scans, there has been a drastic increase in the number of applications based on digital images. This book explores how graphs—which are suitable to represent any discrete data by modeling neighborhood relationships—have emerged as the perfect unified tool to represent, process, and analyze images. It also explains why graphs are ideal for defining graph-theoretical algorithms that enable the processing of functions, making it possible to draw on the rich literature of combinatorial optimization to produce highly efficient solutions. Some key subjects covered in the book include: Definition of graph-theoretical algorithms that enable denoising and image enhancement Energy minimization and modeling of pixel-labeling problems with graph cuts and Markov Random Fields Image processing with graphs: targeted segmentation, partial differential equations, mathematical morphology, and wavelets Analysis of the similarity between objects with graph matching Adaptation and use of graph-theoretical algorithms for specific imaging applications in computational photography, computer vision, and medical and biomedical imaging Use of graphs has become very influential in computer science and has led to many applications in denoising, enhancement, restoration, and object extraction. Accounting for the wide variety of problems being solved with graphs in image processing and computer vision, this book is a contributed volume of chapters written by renowned experts who address specific techniques or applications. This state-of-the-art overview provides application examples that illustrate practical application of theoretical algorithms. Useful as a support for graduate courses in image processing and computer vision, it is also perfect as a reference for practicing engineers working on development and implementation of image processing and analysis algorithms.

Download or read book Time of Flight and Structured Light Depth Cameras written by Pietro Zanuttigh and published by Springer. This book was released on 2016-05-24 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of the key technologies and applications related to new cameras that have brought 3D data acquisition to the mass market. It covers both the theoretical principles behind the acquisition devices and the practical implementation aspects of the computer vision algorithms needed for the various applications. Real data examples are used in order to show the performances of the various algorithms. The performance and limitations of the depth camera technology are explored, along with an extensive review of the most effective methods for addressing challenges in common applications. Applications covered in specific detail include scene segmentation, 3D scene reconstruction, human pose estimation and tracking and gesture recognition. This book offers students, practitioners and researchers the tools necessary to explore the potential uses of depth data in light of the expanding number of devices available for sale. It explores the impact of these devices on the rapidly growing field of depth-based computer vision.

Download or read book Pattern Recognition written by Peng-Yeng Yin and published by BoD – Books on Demand. This book was released on 2008-11-01 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: A wealth of advanced pattern recognition algorithms are emerging from the interdiscipline between technologies of effective visual features and the human-brain cognition process. Effective visual features are made possible through the rapid developments in appropriate sensor equipments, novel filter designs, and viable information processing architectures. While the understanding of human-brain cognition process broadens the way in which the computer can perform pattern recognition tasks. The present book is intended to collect representative researches around the globe focusing on low-level vision, filter design, features and image descriptors, data mining and analysis, and biologically inspired algorithms. The 27 chapters coved in this book disclose recent advances and new ideas in promoting the techniques, technology and applications of pattern recognition.

Download or read book Image and Geometry Processing for 3 D Cinematography written by Rémi Ronfard and published by Springer Science & Business Media. This book was released on 2010-06-29 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: papers, illustrated with examples. They include wavelet bases, implicit functions de ned on a space grid, etc. It appears that a common pattern is the recovery of a controllable model of the scene, such that the resulting images can be edited (interaction). Changing the viewpoint is only one (important) aspect, but changing the lighting and action is equally important [2]. Recording and representing three-dimensional scenes is an emerging technology made possible by the convergence of optics, geometry and computer science, with many applications in the movie industry, and more generally in entertainment. Note that the invention of cinema (camera and projector) was also primarily a scienti c invention that evolved into an art form. We suspect the same thing will probably happen with 3-D movies. 3 Book Contents The book is composed of 12 chapters, which elaborate on the content of talks given at the BANFF workshop. The chapters are organized into three sections. The rst section presents an overview of the inter-relations between the art of cinemat- raphy and the science of image and geometry processing; the second section is devoted to recent developments in geometry; and the third section is devoted to recent developmentsin image processing. 3.1 3-D Cinematography and Applications The rst section of the book presents an overview of the inter-relations between the art of cinematography and the science of image and geometry processing.

Download or read book Advances in Theory and Applications of Stereo Vision written by Asim Bhatti and published by BoD – Books on Demand. This book was released on 2011-01-08 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents a wide range of innovative research ideas and current trends in stereo vision. The topics covered in this book encapsulate research trends from fundamental theoretical aspects of robust stereo correspondence estimation to the establishment of novel and robust algorithms as well as applications in a wide range of disciplines. Particularly interesting theoretical trends presented in this book involve the exploitation of the evolutionary approach, wavelets and multiwavelet theories, Markov random fields and fuzzy sets in addressing the correspondence estimation problem. Novel algorithms utilizing inspiration from biological systems (such as the silicon retina imager and fish eye) and nature (through the exploitation of the refractive index of liquids) make this book an interesting compilation of current research ideas.

Download or read book Computer Vision ECCV 2018 Workshops written by Laura Leal-Taixé and published by Springer. This book was released on 2019-01-22 with total page 743 pages. Available in PDF, EPUB and Kindle. Book excerpt: The six-volume set comprising the LNCS volumes 11129-11134 constitutes the refereed proceedings of the workshops that took place in conjunction with the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.43 workshops from 74 workshops proposals were selected for inclusion in the proceedings. The workshop topics present a good orchestration of new trends and traditional issues, built bridges into neighboring fields, and discuss fundamental technologies and novel applications.

Download or read book Computer Vision ECCV 2016 Workshops written by Gang Hua and published by Springer. This book was released on 2016-11-23 with total page 938 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 9913, LNCS 9914, and LNCS 9915 comprises the refereed proceedings of the Workshops that took place in conjunction with the 14th European Conference on Computer Vision, ECCV 2016, held in Amsterdam, The Netherlands, in October 2016. The three-volume set LNCS 9913, LNCS 9914, and LNCS 9915 comprises the refereed proceedings of the Workshops that took place in conjunction with the 14th European Conference on Computer Vision, ECCV 2016, held in Amsterdam, The Netherlands, in October 2016. 27 workshops from 44 workshops proposals were selected for inclusion in the proceedings. These address the following themes: Datasets and Performance Analysis in Early Vision; Visual Analysis of Sketches; Biological and Artificial Vision; Brave New Ideas for Motion Representations; Joint ImageNet and MS COCO Visual Recognition Challenge; Geometry Meets Deep Learning; Action and Anticipation for Visual Learning; Computer Vision for Road Scene Understanding and Autonomous Driving; Challenge on Automatic Personality Analysis; BioImage Computing; Benchmarking Multi-Target Tracking: MOTChallenge; Assistive Computer Vision and Robotics; Transferring and Adapting Source Knowledge in Computer Vision; Recovering 6D Object Pose; Robust Reading; 3D Face Alignment in the Wild and Challenge; Egocentric Perception, Interaction and Computing; Local Features: State of the Art, Open Problems and Performance Evaluation; Crowd Understanding; Video Segmentation; The Visual Object Tracking Challenge Workshop; Web-scale Vision and Social Media; Computer Vision for Audio-visual Media; Computer VISion for ART Analysis; Virtual/Augmented Reality for Visual Artificial Intelligence; Joint Workshop on Storytelling with Images and Videos and Large Scale Movie Description and Understanding Challenge.