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Motion-Based Recognition by Mubarak Shah,Ramesh Jain Pdf
Motion-based recognition deals with the recognition of an object and/or its motion, based on motion in a series of images. In this approach, a sequence containing a large number of frames is used to extract motion information. The advantage is that a longer sequence leads to recognition of higher level motions, like walking or running, which consist of a complex and coordinated series of events. Unlike much previous research in motion, this approach does not require explicit reconstruction of shape from the images prior to recognition. This book provides the state-of-the-art in this rapidly developing discipline. It consists of a collection of invited chapters by leading researchers in the world covering various aspects of motion-based recognition including lipreading, gesture recognition, facial expression recognition, gait analysis, cyclic motion detection, and activity recognition. Audience: This volume will be of interest to researchers and post- graduate students whose work involves computer vision, robotics and image processing.
Motion Tracking and Gesture Recognition by Carlos Travieso-Gonzalez Pdf
Nowadays, the technological advances allow developing many applications on different fields. In this book Motion Tracking and Gesture Recognition, two important fields are shown. Motion tracking is observed by a hand-tracking system for surgical training, an approach based on detection of dangerous situation by the prediction of moving objects, an approach based on human motion detection results and preliminary environmental information to build a long-term context model to describe and predict human activities, and a review about multispeaker tracking on different modalities. On the other hand, gesture recognition is shown by a gait recognition approach using Kinect sensor, a study of different methodologies for studying gesture recognition on depth images, and a review about human action recognition and the details about a particular technique based on a sensor of visible range and with depth information.
Human Motion Sensing and Recognition by Honghai Liu,Zhaojie Ju,Xiaofei Ji,Chee Seng Chan,Mehdi Khoury Pdf
This book introduces readers to the latest exciting advances in human motion sensing and recognition, from the theoretical development of fuzzy approaches to their applications. The topics covered include human motion recognition in 2D and 3D, hand motion analysis with contact sensors, and vision-based view-invariant motion recognition, especially from the perspective of Fuzzy Qualitative techniques. With the rapid development of technologies in microelectronics, computers, networks, and robotics over the last decade, increasing attention has been focused on human motion sensing and recognition in many emerging and active disciplines where human motions need to be automatically tracked, analyzed or understood, such as smart surveillance, intelligent human-computer interaction, robot motion learning, and interactive gaming. Current challenges mainly stem from the dynamic environment, data multi-modality, uncertain sensory information, and real-time issues. These techniques are shown to effectively address the above challenges by bridging the gap between symbolic cognitive functions and numerical sensing & control tasks in intelligent systems. The book not only serves as a valuable reference source for researchers and professionals in the fields of computer vision and robotics, but will also benefit practitioners and graduates/postgraduates seeking advanced information on fuzzy techniques and their applications in motion analysis.
Human Motion - Understanding, Modeling, Capture and Animation by Ahmed Elgammal,Bodo Rosenhahn,Reinhard Klette Pdf
This book constitutes the refereed proceedings of the Second Workshop on Human Motion, HumanMotion 2007, held in Rio de Janeiro, Brazil October 2007 in conjunction with ICCV 2007. The 22 revised full papers presented were carefully reviewed and selected from 38 submissions. The papers are organized in topical sections on motion capture and pose estimation, body and limb tracking and segmentation and activity recognition.
Motion History Images for Action Recognition and Understanding by Md. Atiqur Rahman Ahad Pdf
Human action analysis and recognition is a relatively mature field, yet one which is often not well understood by students and researchers. The large number of possible variations in human motion and appearance, camera viewpoint, and environment, present considerable challenges. Some important and common problems remain unsolved by the computer vision community. However, many valuable approaches have been proposed over the past decade, including the motion history image (MHI) method. This method has received significant attention, as it offers greater robustness and performance than other techniques. This work presents a comprehensive review of these state-of-the-art approaches and their applications, with a particular focus on the MHI method and its variants.
Computer Vision - ECCV 2008 by David Forsyth,Philip Torr,Andrew Zisserman Pdf
The four-volume set comprising LNCS volumes 5302/5303/5304/5305 constitutes the refereed proceedings of the 10th European Conference on Computer Vision, ECCV 2008, held in Marseille, France, in October 2008. The 243 revised papers presented were carefully reviewed and selected from a total of 871 papers submitted. The four books cover the entire range of current issues in computer vision. The papers are organized in topical sections on recognition, stereo, people and face recognition, object tracking, matching, learning and features, MRFs, segmentation, computational photography and active reconstruction.
Machine Learning for Vision-Based Motion Analysis by Liang Wang,Guoying Zhao,Li Cheng,Matti Pietikäinen Pdf
Techniques of vision-based motion analysis aim to detect, track, identify, and generally understand the behavior of objects in image sequences. With the growth of video data in a wide range of applications from visual surveillance to human-machine interfaces, the ability to automatically analyze and understand object motions from video footage is of increasing importance. Among the latest developments in this field is the application of statistical machine learning algorithms for object tracking, activity modeling, and recognition. Developed from expert contributions to the first and second International Workshop on Machine Learning for Vision-Based Motion Analysis, this important text/reference highlights the latest algorithms and systems for robust and effective vision-based motion understanding from a machine learning perspective. Highlighting the benefits of collaboration between the communities of object motion understanding and machine learning, the book discusses the most active forefronts of research, including current challenges and potential future directions. Topics and features: provides a comprehensive review of the latest developments in vision-based motion analysis, presenting numerous case studies on state-of-the-art learning algorithms; examines algorithms for clustering and segmentation, and manifold learning for dynamical models; describes the theory behind mixed-state statistical models, with a focus on mixed-state Markov models that take into account spatial and temporal interaction; discusses object tracking in surveillance image streams, discriminative multiple target tracking, and guidewire tracking in fluoroscopy; explores issues of modeling for saliency detection, human gait modeling, modeling of extremely crowded scenes, and behavior modeling from video surveillance data; investigates methods for automatic recognition of gestures in Sign Language, and human action recognition from small training sets. Researchers, professional engineers, and graduate students in computer vision, pattern recognition and machine learning, will all find this text an accessible survey of machine learning techniques for vision-based motion analysis. The book will also be of interest to all who work with specific vision applications, such as surveillance, sport event analysis, healthcare, video conferencing, and motion video indexing and retrieval.
Audio- and Video-Based Biometric Person Authentication by Josef Bigun,Fabrizio Smeraldi Pdf
This book constitutes the refereed proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication, AVBPA 2001, held in Halmstad, Sweden in June 2001.The 51 revised papers presented together with three invited papers were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on face as biometrics; face image processing; speech as biometrics and speech processing; fingerprints as biometrics; gait as biometrics; and hand, signature, and iris as biometrics.
Structural, Syntactic, and Statistical Pattern Recognition by Dit-Yan Yeung,James T. Kwok,Ana Fred,Fabio Roli,Dick de Ridder Pdf
This is the proceedings of the 11th International Workshop on Structural and Syntactic Pattern Recognition, SSPR 2006 and the 6th International Workshop on Statistical Techniques in Pattern Recognition, SPR 2006, held in Hong Kong, August 2006 alongside the Conference on Pattern Recognition, ICPR 2006. 38 revised full papers and 61 revised poster papers are included, together with 4 invited papers covering image analysis, character recognition, bayesian networks, graph-based methods and more.
Progress in Pattern Recognition, Image Analysis and Applications by Alberto Sanfeliu,Manuel Lazo Cortés Pdf
This book constitutes the refereed proceedings of the 10th Iberoamerican Congress on Pattern Recognition, CIARP 2005, held in Havana, Cuba in November 2005. The 107 revised full papers presented together with 3 keynote articles were carefully reviewed and selected from more than 200 submissions. The papers cover ongoing research and mathematical methods for pattern recognition, image analysis, and applications in such diverse areas as computer vision, robotics, industry, health, entertainment, space exploration, telecommunications, data mining, document analysis, and natural language processing and recognition.
Face Detection and Gesture Recognition for Human-Computer Interaction by Ming-Hsuan Yang,Narendra Ahuja Pdf
Traditionally, scientific fields have defined boundaries, and scientists work on research problems within those boundaries. However, from time to time those boundaries get shifted or blurred to evolve new fields. For instance, the original goal of computer vision was to understand a single image of a scene, by identifying objects, their structure, and spatial arrangements. This has been referred to as image understanding. Recently, computer vision has gradually been making the transition away from understanding single images to analyzing image sequences, or video understanding. Video understanding deals with understanding of video sequences, e. g. , recognition of gestures, activities, facial expressions, etc. The main shift in the classic paradigm has been from the recognition of static objects in the scene to motion-based recognition of actions and events. Video understanding has overlapping research problems with other fields, therefore blurring the fixed boundaries. Computer graphics, image processing, and video databases have obvious overlap with computer vision. The main goal of computer graphics is to gener ate and animate realistic looking images, and videos. Researchers in computer graphics are increasingly employing techniques from computer vision to gen erate the synthetic imagery. A good example of this is image-based rendering and modeling techniques, in which geometry, appearance, and lighting is de rived from real images using computer vision techniques. Here the shift is from synthesis to analysis followed by synthesis.
Computer Vision - ECCV 2008 by David Hutchison,David Forsyth,Takeo Kanade,Josef Kittler,Jon M. Kleinberg,Friedemann Mattern,John C. Mitchell,Moni Naor,Oscar Nierstrasz,C. Pandu Rangan,Bernhard Steffen,Madhu Sudan,Demetri Terzopoulos,Philip Torr,Doug Tygar,Moshe Y. Vardi,Gerhard Weikum,Andrew Zisserman Pdf
The four-volume set comprising LNCS volumes 5302/5303/5304/5305 constitutes the refereed proceedings of the 10th European Conference on Computer Vision, ECCV 2008, held in Marseille, France, in October 2008. The 243 revised papers presented were carefully reviewed and selected from a total of 871 papers submitted. The four books cover the entire range of current issues in computer vision. The papers are organized in topical sections on recognition, stereo, people and face recognition, object tracking, matching, learning and features, MRFs, segmentation, computational photography and active reconstruction.
Computer Recognition Systems by Marek Kurzynski,Edward Puchala,Michal Wozniak,Andrzej Zolnierek Pdf
th This book contains papers accepted for presentation at the 4 International Conference on Computer Recognition Systems CORES'05, May 22-25, 2005, Rydzyna Castle (Poland), This conference is a continuation of a series of con ferences on similar topics (KOSYR) organized each second year, since 1999, by the Chair of Systems and Computer Networks, Wroclaw University of Tech nology. An increasing interest to those conferences paid not only by home but also by foreign participants inspired the organizers to transform them into conferences of international range. Our expectations that the community of specialists in computer recognizing systems will find CORES'05 a proper form of maintaining the tradition of the former conferences have been confirmed by a large number of submitted papers. Alas, organizational constraints caused a necessity to narrow the acceptance criteria so that only 100 papers have been finally included into the conference program. The area covered by accepted papers is still very large and it shows how vivacious is scientific activity in the domain of computer recognition methods and systems. It contains vari ous theoretical approaches to the recognition problem based on mathematical statistics, fuzzy sets, morphological methods, wavelets, syntactic methods, genetic algorithms, artificial neural networks, ontological models, etc. Most attention is still paid to visual objects recognition; however, acoustic, tex tual and other objects are also considered. Among application areas medical problems are in majority; recognition of faces, speech signals and textual in formation processing methods being also investigated.
Pattern Recognition and Image Analysis by Jorge S. Marques Pdf
The two-volume set LNCS 3522 and 3523 constitutes the refereed proceedings of the Second Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2005, held in Estoril, Portugal in June 2005. The 170 revised full papers presented were carefully reviewed and selected from 292 submissions. The papers are organized in topical sections on computer vision, shape and matching, image and video processing, image and video coding, face recognition, human activity analysis, surveillance, robotics, hardware architectures, statistical pattern recognition, syntactical pattern recognition, image analysis, document analysis, bioinformatics, medical imaging, biometrics, speech recognition, natural language analysis, and applications.
