Download or read book Automatic 3D Face Reconstruction and Tracking Using Consumer RGB D Camera written by Zhong Li and published by . This book was released on 2015 with total page 51 pages. Available in PDF, EPUB and Kindle. Book excerpt: 3D face reconstruction and tracking has become an important research topic during the past few decades in both computer graphics and computer vision. Researchers are seeking for a method to model the human face using a low cost device with high quality. Currently, face models can be captured by expensive active sensor-like laser scanning; however, this sensor technology is not affordable for everyone and experiments must be conducted under certain conditions. In our thesis, we present an automatic 3D face reconstruction and pose estimation framework using a consumer depth camera. Our method does not require any prior face model database. We acquire location of human face part using regular face detector, and in order to generate a high quality face model, we integrate and register information from multiple frames together, which allows detection of noise. In addition, by detecting 2D landmark information provided by the RGB image, we are able to find correspondence in the 3D model. Results are demonstrated by visual inspection. Future application for our research may involve game design and face avatar generation.

Download or read book Optimization of Pose Texture and Geometry in 3d Reconstruction with Consumer Depth Cameras written by Chao Wang (Computer graphics engineer) and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 3D Reconstruction is one of the most popular topics in the area of computer graphics and vision. A typical 3D reconstruction process is to reconstruct the 3D model or other similar geometry representations from different sources of data, including color images and depth data captured by depth cameras. Online and offline RGB-D (RGB and depth) reconstruction techniques have been developing rapidly in this decade with the prevalence of consumer depth cameras. However, current 3D construction methods still lack robustness in the tracking process, and also pay little attention on the quality of final reconstructed 3D models. This dissertation is focused on improving the robustness of camera tracking in the online RGB-D reconstruction process, as well as optimizing camera pose, face texture and geometry quality of 3D models in the offline RGB-D reconstruction with consumer depth cameras. One problem in online 3D reconstruction is that, existing camera pose estimation approaches in online RGB-D reconstruction systems always suffer from fast-scanned data and generate inaccurate relative transformations between consecutive frames. In order to improve the tracking robustness of online 3D reconstruction, we propose a novel feature-based camera pose optimization algorithm for real-time 3D reconstruction systems. We have demonstrated that our method improves current methods by utilizing matched features across all frames, and is robust on reconstructing RGB-D data with large adjacent shifts across frames. Another problem in RGB-D reconstruction is that the geometry of reconstructed 3D models is usually too dense and coarse, and texture quality of mesh faces is always too low. To deal with this problem, we introduce a new plane-based RGB-D reconstruction approach with plane, geometry and texture optimization to improve the geometry and texture quality of reconstructed models. Compared to existing planar reconstruction methods which cover only large planar regions in the scene, our method reconstructs the entire original scene without losing geometry details in the low-polygonal lightweight result meshes with clear face textures and sharp features. We have demonstrated the effectiveness of our approach by applying it onto different RGB-D benchmarks and comparing it with other state-of-the-art reconstruction methods.

Download or read book Pattern Recognition and Machine Intelligence written by Marzena Kryszkiewicz and published by Springer. This book was released on 2015-06-22 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 6th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2015, held in Warsaw, Poland, in June/July 2015. The total of 53 full papers and 1 short paper presented in this volume were carefully reviewed and selected from 90 submissions. They were organized in topical sections named: foundations of machine learning; image processing; image retrieval; image tracking; pattern recognition; data mining techniques for large scale data; fuzzy computing; rough sets; bioinformatics; and applications of artificial intelligence.

Download or read book 3D Facial Performance Capture From A Single RGBD Camera written by Yen-Lin Chen and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Realistic facial animation remains one of the most challenging problems in computer graphics, where facial performance capture of real people has been a key component. The current state-of-the-art technologies used to capture facial performances are far too expensive and cumbersome for general users, which limits the potential applications of performance capture. The primary contribution of this dissertation is to propose two systems that are suitable for common users to capture facial performance using a single low-cost device. Our first system focuses on large-scale facial performance reconstruction from a single RGBD image. Our goal is to accurately reconstruct global transformation, as well as large-scale deformations from the images provided by a single shot of a Microsoft Kinect camera. With the combination of a robust facial feature detector and an image-based registration method, our system is automatic, robust and accurate to reconstruct facial movements. The result face meshes are topology consistent and with dense correspondences. Since people are natural experts of native human expressions and can distinguish subtle differences, e.g. dynamic facial wrinkles, we propose a second system combining our performance capture with a 3D scanning system to add person-specific high-resolution details in an efficient and effective way. We demonstrate the power of our proposed systems by testing on both real and synthetic data, as well as a commercially available motion capture system. Results show that the proposed systems generate believable and comparable results. We believe the proposed systems should be useful and applicable for general as well as professional users. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/152446

Download or read book 3D Face Modeling with a Consumer Depth Camera written by and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Vision Based Human Activity Recognition written by Zhongxu Hu and published by Springer Nature. This book was released on 2022-04-22 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a systematic, comprehensive, and timely review on V-HAR, and it covers the related tasks, cutting-edge technologies, and applications of V-HAR, especially the deep learning-based approaches. The field of Human Activity Recognition (HAR) has become one of the trendiest research topics due to the availability of various sensors, live streaming of data and the advancement in computer vision, machine learning, etc. HAR can be extensively used in many scenarios, for example, medical diagnosis, video surveillance, public governance, also in human–machine interaction applications. In HAR, various human activities such as walking, running, sitting, sleeping, standing, showering, cooking, driving, abnormal activities, etc., are recognized. The data can be collected from wearable sensors or accelerometer or through video frames or images; among all the sensors, vision-based sensors are now the most widely used sensors due to their low-cost, high-quality, and unintrusive characteristics. Therefore, vision-based human activity recognition (V-HAR) is the most important and commonly used category among all HAR technologies. The addressed topics include hand gestures, head pose, body activity, eye gaze, attention modeling, etc. The latest advancements and the commonly used benchmark are given. Furthermore, this book also discusses the future directions and recommendations for the new researchers.

Download or read book Consumer Depth Cameras for Computer Vision written by Andrea Fossati and published by Springer Science & Business Media. This book was released on 2012-10-04 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: The potential of consumer depth cameras extends well beyond entertainment and gaming, to real-world commercial applications. This authoritative text reviews the scope and impact of this rapidly growing field, describing the most promising Kinect-based research activities, discussing significant current challenges, and showcasing exciting applications. Features: presents contributions from an international selection of preeminent authorities in their fields, from both academic and corporate research; addresses the classic problem of multi-view geometry of how to correlate images from different viewpoints to simultaneously estimate camera poses and world points; examines human pose estimation using video-rate depth images for gaming, motion capture, 3D human body scans, and hand pose recognition for sign language parsing; provides a review of approaches to various recognition problems, including category and instance learning of objects, and human activity recognition; with a Foreword by Dr. Jamie Shotton.

Download or read book Real time Dense 3D Reconstruction with RGB D Camera written by Hanyu Deng and published by . This book was released on 2019 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Automatic 3D Face Reconstruction and Feature Transfer written by Marcel Piotraschke and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Three dimensional Environment Reconstruction and Object Tracking Using RGB D Sensing of Stereo Camera written by 洪中易 and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book 3D Face Reconstruction and Emotion Analytics with Part based Morphable Models written by Hai Jin and published by . This book was released on 2018 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: 3D face reconstruction and facial expression analytics using 3D facial data are new and hot research topics in computer graphics and computer vision. In this proposal, we first review the background knowledge for emotion analytics using 3D morphable face model, including geometry feature-based methods, statistic model-based methods and more advanced deep learning-bade methods. Then, we introduce a novel 3D face modeling and reconstruction solution that robustly and accurately acquires 3D face models from a couple of images captured by a single smartphone camera. Two selfie photos of a subject taken from the front and side are used to guide our Non-Negative Matrix Factorization (NMF) induced part-based face model to iteratively reconstruct an initial 3D face of the subject. Then, an iterative detail updating method is applied to the initial generated 3D face to reconstruct facial details through optimizing lighting parameters and local depths. Our iterative 3D face reconstruction method permits fully automatic registration of a part-based face representation to the acquired face data and the detailed 2D/3D features to build a high-quality 3D face model. The NMF part-based face representation learned from a 3D face database facilitates effective global and adaptive local detail data fitting alternatively. Our system is flexible and it allows users to conduct the capture in any uncontrolled environment. We demonstrate the capability of our method by allowing users to capture and reconstruct their 3D faces by themselves. Based on the 3D face model reconstruction, we can analyze the facial expression and the related emotion in 3D space. We present a novel approach to analyze the facial expressions from images and a quantitative information visualization scheme for exploring this type of visual data.

Download or read book Full 3D Reconstruction From Multiple RGB D Cameras written by Owen Watson and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Each pair is aligned by a two-phase procedure that transforms the data from the coordinate system of the camera at a lower level in the alignment tree to that of the higher. The transformation between each pair is catalogued and used to reconstruction of incoming frames from the cameras. Once calibrated, cameras are assumed to be independent and their successive frames are compared to detect motion. The catalogued transformations are updated on instances that motion is detected essentially correcting misalignment. \par At the end of the calibration process the reconstructed scene generated from the combined data would contain relative alignment accuracy throughout all regions. Using this proposed algorithm reconstruction accuracy of over 90% was achieved for systems calibrated with the angle between the cameras 45 degrees or more. Once calibrated the cameras can observe and reconstruct a scene on every frame. This is reliant on the assumption that the cameras will be fixed; however, in a practical sense this cannot be guaranteed. Systems maintained over 90% reconstruction accuracy during operation with induced misalignment. This procedure also maintained the reconstruction accuracy from calibration during execution for up to an hour. The fundamental contribution of this work is the novel concept of using overlap as a means of expressing how a group of cameras are connected. Building a spanning tree representation of the given system of cameras provides a useful structure for uniquely expressing the relationship between the cameras. A calibration procedure that is effective with low overlapping views is also contributed. The final contribution is a procedure to maintain reconstruction accuracy overtime in a mostly static environment.

Download or read book Data driven Approaches for Personalized Head Reconstruction written by Shu Liang and published by . This book was released on 2018 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: Personalized 3D face reconstruction has produced exciting results over the past few years. However, traditional methods usually require complicated setups or controlled environments to get the detailed shape of a person's face. Most methods focus solely on the face area and mask out the hair due to the non-rigid nature and complicated layer structure of hairstyles. In this work, we explore data-driven approaches to reconstruct a person's 3D face or head including the hair from the devices that can be easily accessed by everyone.The first part of our work introduces an algorithm that takes a single frame of a person's face from a commercial depth camera Kinect and produces a high-resolution 3D mesh of the input leveraging a large research dataset of 3D face meshes. We divide the input depth frame into semantically significant regions (eyes, nose, mouth, cheeks) and search the database for the best matching shape per region. We further combine the input depth frame with the matched database shapes into a single mesh that results in a high-resolution shape of the input person. In order to free people from the capturing session, the larger portion of this thesis focuses on reconstructing not only the face, but also the rest of the head using in-the-wild image collections and videos. We first introduce a boundary-value growing algorithm to model a person's head from the person's large collection of photo data. We target reconstruction of the rough shape of the head. Our method is to gradually "grow" the head mesh starting from the frontal face and extending to the rest of the views using photometric stereo constraints. Results on photos of celebrities downloaded from the Internet are given. However, in this algorithm, we have not reconstructed a complete head model and a specific model of the hair is lacked. We further utilize a person's in-the-wild video to recover the full head model considering the multi-view information and hairstyle consistency across video frames. Given a video of a person's head, e.g., a TV interview, our method automatically reconstructs a 3D hair model leveraging a 3D hairstyle database. The resultant 3D hair model can be later deformed to change the hair shape, to make it brighter or darker. Our head reconstruction also includes facial modeling from the video, which is used to combine with the hair model. The method is completely automatic and requires as input only a single video taken "in the wild", found as is on the web or a selfie video taken by a smart phone. We demonstrate the capability of our method on a variety of celebrity videos and selfie videos, as well as comparing to the state of the art.

Download or read book Accurate Efficient and Robust 3D Reconstruction of Static and Dynamic Objects written by Kyoung-Rok Lee and published by . This book was released on 2014 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt: 3D reconstruction is the method of creating the shape and appearance of a real scene or objects, given a set of images on the scene. Realistic scene or object reconstruction is essential in many applications such as robotics, computer graphics, Tele- Immersion (TI), and Augmented Reality (AR). This thesis explores accurate, efficient, and robust methods for the 3D reconstruction of static and dynamic objects from RGB-D images. For accurate 3D reconstruction, the depth maps should have high geometric quality and resolution. However, depth maps are often captured at low-quality or low resolution, due to either sensor hardware limitations or errors in estimation. A new sampling-based robust multi-lateral filtering method is proposed herein to improve the resolution and quality of depth data. The enhancement is achieved by selecting reliable depth samples from a neighborhood of pixels and applying multi-lateral filtering using colored images that are both high-quality and high-resolution. Camera pose estimation is one of the most important operations in 3D reconstruction, since any minor error in this process may distort the resulting reconstruction. We present a robust method for camera tracking and surface mapping using a handheld RGB-D camera, which is effective for challenging situations such as during fast camera motion or in geometrically featureless scenes. This is based on the quaternion-based orientation estimation method for initial sparse estimation and a weighted Iterative Closest Point (ICP) method for dense estimation to achieve a better rate of convergence for both the optimization and accuracy of the resulting trajectory. We present a novel approach for the reconstruction of static object/scene with realistic surface geometry using a handheld RGB-D camera. To obtain high-resolution RGB images, an additional HD camera is attached to the top of a Kinect and is calibrated to reconstruct a 3D model with realistic surface geometry and high-quality color textures. We extend our depth map refinement method by utilizing high frequency information in color images to recover finer-scale surface geometry. In addition, we use our robust camera pose estimation to estimate the orientation of the camera in the global coordinate system accurately. For the reconstruction of moving objects, a novel dynamic scene reconstruction system using multiple commodity depth cameras is proposed. Instead of using expensive multi-view scene capturing setups, our system only requires four Kinects, which are carefully located to generate full 3D surface models of objects. We introduce a novel depth synthesis method for point cloud densification and noise removal in the depth data. In addition, a new weighting function is presented to overcome the drawbacks of the existing volumetric representation method.

Download or read book RGB D Image Analysis and Processing written by Paul L. Rosin and published by Springer. This book was released on 2019-11-06 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the fundamentals and recent advances in RGB-D imaging as well as covering a range of RGB-D applications. The topics covered include: data acquisition, data quality assessment, filling holes, 3D reconstruction, SLAM, multiple depth camera systems, segmentation, object detection, salience detection, pose estimation, geometric modelling, fall detection, autonomous driving, motor rehabilitation therapy, people counting and cognitive service robots. The availability of cheap RGB-D sensors has led to an explosion over the last five years in the capture and application of colour plus depth data. The addition of depth data to regular RGB images vastly increases the range of applications, and has resulted in a demand for robust and real-time processing of RGB-D data. There remain many technical challenges, and RGB-D image processing is an ongoing research area. This book covers the full state of the art, and consists of a series of chapters by internationally renowned experts in the field. Each chapter is written so as to provide a detailed overview of that topic. RGB-D Image Analysis and Processing will enable both students and professional developers alike to quickly get up to speed with contemporary techniques, and apply RGB-D imaging in their own projects.

Download or read book Analysis and Modeling of Faces and Gestures written by S. Kevin Zhou and published by Springer. This book was released on 2007-11-04 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Workshop on Analysis and Modelling of Faces and Gestures, AMFG 2007, held within the scope of ICCV 2007, the International Conference on Computer Vision. The papers review the status of recognition, analysis and modeling of face, gesture, activity, and behavior. Topics addressed include feature representation, 3D face, video-based face recognition, facial motion analysis, and sign recognition.

Download or read book Experimental Robotics VIII written by Bruno Siciliano and published by Springer Science & Business Media. This book was released on 2003-01-21 with total page 671 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of papers on the state of the art in experimental robotics. Experimental Robotics is at the core of validating robotics research for both its systems science and theoretical foundations. Because robotics experiments are carried out on physical, complex machines, of which its controllers are subject to uncertainty, devising meaningful experiments and collecting statistically significant results, pose important and unique challenges in robotics. Robotics experiments serve as a unifying theme for robotics system science and algorithmic foundations. These observations have led to the creation of the International Symposia on Experimental Robotics. The papers in this book were presented at the 2002 International Symposium on Experimental Robotics.