Download or read book Classification of Moving Objects and Recognition of Human Activity Using Infrared Surveillance Sensors written by Jakir Hossen and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear pyroelectric array sensors have enabled useful classifications of objects such as humans and animals to be performed with relatively low cost hardware in border and perimeter security applications. Ongoing research has sought to improve the performance of these sensors through signal processing algorithms. In this thesis, we introduce the use of Hidden Markov Tree (HMT) models for object recognition in images generated by linear pyroelectric sensors. HMTs are trained to statistically model the wavelet features of individual objects through an expectation-maximization (EM) learning process. Human versus animal classification for a test object is made by evaluating its wavelet features against the trained HMTs using the maximum-likelihood (ML) criterion. The classification performance of this approach is compared to two other techniques; a texture, shape, and spectral component feature (TSSF) based classifier and a speeded up robust feature (SURF) based classifier. The evaluation indicates that among the three techniques, the wavelet based HMT model works well, is robust, and has improved classification performance compared to a SURF features based algorithm in equivalent computation time. When compared to the TSSF based classifier, the HMT model has slightly degraded performance but almost an order of magnitude improvement in computation time enabling real time implementation. A second goal of this research is to classify the activity of objects identified as human. If the linear pyroelectric array sensor identifies the object as human, this then triggers a thermal video camera to capture video. From the video then, the goal is to recognize the activity as either suspicious or not based on a stored activity database. Recognition of human activity is crucial for surveillance and monitoring systems. In this thesis, we investigate the recognition of motion based activity in thermal infrared video. The segmentation of human poses or motions from known or unknown backgrounds is always a challenging task due to the lighting conditions and the colors of clothing and surfaces. ViBe: A universal background segmentation technique has been employed to improve the pose segmentation from the background. We have proposed a contrast based spatio-temporal template named temporal contrast image (TCI) which can capture small motion and is useful for repetitive and non-repetitive activity recognition. Hu's moment invariant feature descriptor and Naive Bayesian classifier are used for activity recognition. We have also combined our approach with existing spatio-temporal image formation techniques such as the gait energy image (GEI), motion energy image (MEI) and motion history image (MHI) for performance comparison. Experimental results on a limited set of activities demonstrate the effectiveness of our proposed approach. The method proposed in this work outperforms the statistical method for non-repetitive activity recognition. The overall goal of this research is to create a simple surveillance system that has real time moving object detection together with classification and human activity recognition. The profiling sensors described in this dissertation are relatively simple devices when compared to typical imaging cameras.

Download or read book Advances in Human Activity Detection and Recognition HADR Systems written by Santosh Kumar Tripathy and published by Springer Nature. This book was released on with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Augmented Vision Perception in Infrared written by Riad I. Hammoud and published by Springer Science & Business Media. This book was released on 2009-01-01 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: Throughout much of machine vision’s early years the infrared imagery has suffered from return on investment despite its advantages over visual counterparts. Recently, the ?scal momentum has switched in favor of both manufacturers and practitioners of infrared technology as a result of today’s rising security and safety challenges and advances in thermographic sensors and their continuous drop in costs. This yielded a great impetus in achieving ever better performance in remote surveillance, object recognition, guidance, noncontact medical measurements, and more. The purpose of this book is to draw attention to recent successful efforts made on merging computer vision applications (nonmilitary only) and nonvisual imagery, as well as to ?ll in the need in the literature for an up-to-date convenient reference on machine vision and infrared technologies. Augmented Perception in Infrared provides a comprehensive review of recent deployment of infrared sensors in modern applications of computer vision, along with in-depth description of the world’s best machine vision algorithms and intel- gent analytics. Its topics encompass many disciplines of machine vision, including remote sensing, automatic target detection and recognition, background modeling and image segmentation, object tracking, face and facial expression recognition, - variant shape characterization, disparate sensors fusion, noncontact physiological measurements, night vision, and target classi?cation. Its application scope includes homeland security, public transportation, surveillance, medical, and military. Mo- over, this book emphasizes the merging of the aforementioned machine perception applications and nonvisual imaging in intensi?ed, near infrared, thermal infrared, laser, polarimetric, and hyperspectral bands.

Download or read book Human Activity Recognition Using Time Series Classification written by Zhino Yousefi and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Biometrics Concepts Methodologies Tools and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2016-08-30 with total page 1887 pages. Available in PDF, EPUB and Kindle. Book excerpt: Security and authentication issues are surging to the forefront of the research realm in global society. As technology continues to evolve, individuals are finding it easier to infiltrate various forums and facilities where they can illegally obtain information and access. By implementing biometric authentications to these forums, users are able to prevent attacks on their privacy and security. Biometrics: Concepts, Methodologies, Tools, and Applications is a multi-volume publication highlighting critical topics related to access control, user identification, and surveillance technologies. Featuring emergent research on the issues and challenges in security and privacy, various forms of user authentication, biometric applications to image processing and computer vision, and security applications within the field, this publication is an ideal reference source for researchers, engineers, technology developers, students, and security specialists.

Download or read book Multi camera Human Activity Recognition in Unconstrained Indoor and Outdoor Environments written by Robert Bodor and published by . This book was released on 2005 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Human Activity Recognition and Behaviour Analysis written by Liming Chen and published by Springer. This book was released on 2019-06-11 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book first defines the problems, various concepts and notions related to activity recognition, and introduces the fundamental rationale and state-of-the-art methodologies and approaches. It then describes the use of artificial intelligence techniques and advanced knowledge technologies for the modelling and lifecycle analysis of human activities and behaviours based on real-time sensing observations from sensor networks and the Internet of Things. It also covers inference and decision-support methods and mechanisms, as well as personalization and adaptation techniques, which are required for emerging smart human-machine pervasive systems, such as self-management and assistive technologies in smart healthcare. Each chapter includes theoretical background, technological underpinnings and practical implementation, and step-by-step information on how to address and solve specific problems in topical areas. This monograph can be used as a textbook for postgraduate and PhD students on courses such as computer systems, pervasive computing, data analytics and digital health. It is also a valuable research reference resource for postdoctoral candidates and academics in relevant research and application domains, such as data analytics, smart cities, smart energy, and smart healthcare, to name but a few. Moreover, it offers smart technology and application developers practical insights into the use of activity recognition and behaviour analysis in state-of-the-art cyber-physical systems. Lastly, it provides healthcare solution developers and providers with information about the opportunities and possible innovative solutions for personalized healthcare and stratified medicine.

Download or read book Behavioral Biometrics for Human Identification Intelligent Applications written by Wang, Liang and published by IGI Global. This book was released on 2009-08-31 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This edited book provides researchers and practitioners a comprehensive understanding of the start-of-the-art of behavioral biometrics techniques, potential applications, successful practice, and available resources"--Provided by publisher.

Download or read book Human Localization and Activity Recognition Using Distributed Motion Sensors written by Dharmendra Chandrashekar Kallur and published by . This book was released on 2014 with total page 75 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this thesis is to localize a human and recognize his/her activities in indoor environments using distributed motion sensors. We propose to use a test bed simulated as mock apartment for conducting our experiments. The two parts of the thesis are localization and activity recognition of the elderly person. We explain complete hardware and software setup used to provide these services. The hardware setup consists of two types of sensor end nodes and two sink nodes. The two types of end nodes are Passive Infrared sensor node and GridEye sensor node. Passive Infrared sensor nodes consist of Passive Infrared sensors for motion detection. GridEye sensor nodes consist of thermal array sensors. Data from these sensors are acquired using Arduino boards and transmitted using Xbee modules to the sink nodes. The sink nodes consist of receiver Xbee modules connected to a computer. The sensor nodes were strategically placed at different place inside the apartment. The thermal array sensor provides 64 pixel temperature values, while the PIR sensor provides binary information about motion in its field of view. Since the thermal array sensor provides more information, they were placed in large rooms such as living room and bed room. While PIR sensors were placed in kitchen and bathroom. Initially GridEye sensors are calibrated to obtain the transformation between pixel and real world coordinates. Data from these sensors were processed on computer and we were able to localize the human inside the apartment. We compared the location accuracy using ground truth data obtained from the OptiTrack system. GridEye sensors were also used for activity recognition. Basic human activities such as sitting, sleeping, standing and walking were recognized. We used Support Vector Machine (SVM) to recognize sitting and sleeping activities. Gait speed of human was used to recognize the standing and walking activities. Experiments were performed to obtain the accuracy of classification for these activities.

Download or read book Learning to Analyze what is Beyond the Visible Spectrum written by Amanda Berg and published by Linköping University Electronic Press. This book was released on 2019-11-13 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thermal cameras have historically been of interest mainly for military applications. Increasing image quality and resolution combined with decreasing camera price and size during recent years have, however, opened up new application areas. They are now widely used for civilian applications, e.g., within industry, to search for missing persons, in automotive safety, as well as for medical applications. Thermal cameras are useful as soon as there exists a measurable temperature difference. Compared to cameras operating in the visual spectrum, they are advantageous due to their ability to see in total darkness, robustness to illumination variations, and less intrusion on privacy. This thesis addresses the problem of automatic image analysis in thermal infrared images with a focus on machine learning methods. The main purpose of this thesis is to study the variations of processing required due to the thermal infrared data modality. In particular, three different problems are addressed: visual object tracking, anomaly detection, and modality transfer. All these are research areas that have been and currently are subject to extensive research. Furthermore, they are all highly relevant for a number of different real-world applications. The first addressed problem is visual object tracking, a problem for which no prior information other than the initial location of the object is given. The main contribution concerns benchmarking of short-term single-object (STSO) visual object tracking methods in thermal infrared images. The proposed dataset, LTIR (Linköping Thermal Infrared), was integrated in the VOT-TIR2015 challenge, introducing the first ever organized challenge on STSO tracking in thermal infrared video. Another contribution also related to benchmarking is a novel, recursive, method for semi-automatic annotation of multi-modal video sequences. Based on only a few initial annotations, a video object segmentation (VOS) method proposes segmentations for all remaining frames and difficult parts in need for additional manual annotation are automatically detected. The third contribution to the problem of visual object tracking is a template tracking method based on a non-parametric probability density model of the object's thermal radiation using channel representations. The second addressed problem is anomaly detection, i.e., detection of rare objects or events. The main contribution is a method for truly unsupervised anomaly detection based on Generative Adversarial Networks (GANs). The method employs joint training of the generator and an observation to latent space encoder, enabling stratification of the latent space and, thus, also separation of normal and anomalous samples. The second contribution is the previously unaddressed problem of obstacle detection in front of moving trains using a train-mounted thermal camera. Adaptive correlation filters are updated continuously and missed detections of background are treated as detections of anomalies, or obstacles. The third contribution to the problem of anomaly detection is a method for characterization and classification of automatically detected district heat leakages for the purpose of false alarm reduction. Finally, the thesis addresses the problem of modality transfer between thermal infrared and visual spectrum images, a previously unaddressed problem. The contribution is a method based on Convolutional Neural Networks (CNNs), enabling perceptually realistic transformations of thermal infrared to visual images. By careful design of the loss function the method becomes robust to image pair misalignments. The method exploits the lower acuity for color differences than for luminance possessed by the human visual system, separating the loss into a luminance and a chrominance part.

Download or read book Computer Vision in the Infrared Spectrum written by Michael Teutsch and published by Springer Nature. This book was released on 2022-06-01 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human visual perception is limited to the visual-optical spectrum. Machine vision is not. Cameras sensitive to the different infrared spectra can enhance the abilities of autonomous systems and visually perceive the environment in a holistic way. Relevant scene content can be made visible especially in situations, where sensors of other modalities face issues like a visual-optical camera that needs a source of illumination. As a consequence, not only human mistakes can be avoided by increasing the level of automation, but also machine-induced errors can be reduced that, for example, could make a self-driving car crash into a pedestrian under difficult illumination conditions. Furthermore, multi-spectral sensor systems with infrared imagery as one modality are a rich source of information and can provably increase the robustness of many autonomous systems. Applications that can benefit from utilizing infrared imagery range from robotics to automotive and from biometrics to surveillance. In this book, we provide a brief yet concise introduction to the current state-of-the-art of computer vision and machine learning in the infrared spectrum. Based on various popular computer vision tasks such as image enhancement, object detection, or object tracking, we first motivate each task starting from established literature in the visual-optical spectrum. Then, we discuss the differences between processing images and videos in the visual-optical spectrum and the various infrared spectra. An overview of the current literature is provided together with an outlook for each task. Furthermore, available and annotated public datasets and common evaluation methods and metrics are presented. In a separate chapter, popular applications that can greatly benefit from the use of infrared imagery as a data source are presented and discussed. Among them are automatic target recognition, video surveillance, or biometrics including face recognition. Finally, we conclude with recommendations for well-fitting sensor setups and data processing algorithms for certain computer vision tasks. We address this book to prospective researchers and engineers new to the field but also to anyone who wants to get introduced to the challenges and the approaches of computer vision using infrared images or videos. Readers will be able to start their work directly after reading the book supported by a highly comprehensive backlog of recent and relevant literature as well as related infrared datasets including existing evaluation frameworks. Together with consistently decreasing costs for infrared cameras, new fields of application appear and make computer vision in the infrared spectrum a great opportunity to face nowadays scientific and engineering challenges.

Download or read book Proceedings of Eighth International Congress on Information and Communication Technology written by Xin-She Yang and published by Springer Nature. This book was released on 2023-07-29 with total page 1110 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers selected high-quality research papers presented at the Eighth International Congress on Information and Communication Technology, held at Brunel University, London, on 20–23 February 2023. It discusses emerging topics pertaining to information and communication technology (ICT) for managerial applications, e-governance, e-agriculture, e-education and computing technologies, the Internet of Things (IoT) and e-mining. Written by respected experts and researchers working on ICT, the book offers a valuable asset for young researchers involved in advanced studies. The work is presented in four volumes.

Download or read book Robust Human Activity Classification and Motion Monitoring Systems Using Inertial Sensors written by Xiaoxu Wu and published by . This book was released on 2016 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proliferation of powerful microcomputers and the development of modern machine learning tools have enabled human daily activity monitoring systems using wearable inertial sensor like accelerometers and gyroscopes. These systems fulfilled the urgent need in health and wellness industries in helping doctors and clinicians during diagnosis, treatments and rehabilitation processes for neurological diseases like strokes and Parkinson's. For most current activity monitoring systems, there exists an assumption that the sensors are always securely and correctly mounted by the users. Unfortunately, such assumptions do not hold as the scale of studies increase. And it is especially challenging for subjects with neurological diseases to follow instructions about how to mount the sensors everyday, because some of the elderlies tend to be technophobic and neurological diseases are often accompanied with cognitive difficulties. Errors in sensor mounting pose can cause large amount of data loss and distortion and will affect the robustness of the systems severely. In observance of these issues, a series of solutions for sensor orientation and position errors in human motion monitoring and activity classification will be presented. Opportunistic calibration methods to find the true sensor orientation and position will be discussed. In addition, systems that provide robust monitoring regardless of the exact sensor pose will be proposed.

Download or read book Biomedical Sensing and Analysis written by Iyad Obeid and published by Springer Nature. This book was released on 2022-07-19 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an interdisciplinary look at emerging trends in signal processing and biomedicine found at the intersection of healthcare, engineering, and computer science. Bringing together expanded versions of selected papers presented at the 2020 IEEE Signal Processing in Medicine and Biology Symposium (IEEE SPMB), it examines the vital role signal processing plays in enabling a new generation of technology based on big data and looks at applications ranging from medical electronics to data mining of electronic medical records. Topics covered include analysis of medical images, machine learning, biomedical nanosensors, wireless technologies, and instrumentation and electrical stimulation. Biomedical Sensing and Analysis: Signal Processing in Medicine and Biology presents tutorials and examples of successful applications, and will appeal to a wide range of professionals, researchers, and students interested in applications of signal processing, medicine, and biology. Presents an interdisciplinary look at research trends in signal processing and biomedicine; Promotes collaboration between healthcare practitioners and signal processing researchers; Includes tutorials and examples of successful applications.

Download or read book Detection and Classification of Moving Objects for an Automated Surveillance System written by and published by . This book was released on 2006 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Image and Signal Processing written by Abderrahim Elmoataz and published by Springer Science & Business Media. This book was released on 2008-06-24 with total page 639 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Conference on Image and Signal Processing, ICISP 2008, held in Cherbourg-Octeville, France, in July 2008. The 48 revised full papers and 22 revised poster papers presented were carefully reviewed and selected from 193 submissions. The papers are organized in topical sections on image filtering, image segmentation, computer vision, feature extraction, pattern recognition, graph-based representations, motion detection and estimation, new interfaces, document processing, and signal processing.

Download or read book Body Sensor Networks written by Guang-Zhong Yang and published by Springer. This book was released on 2014-04-16 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: The last decade has witnessed a rapid surge of interest in new sensing and monitoring devices for wellbeing and healthcare. One key development in this area is wireless, wearable and implantable in vivo monitoring and intervention. A myriad of platforms are now available from both academic institutions and commercial organisations. They permit the management of patients with both acute and chronic symptoms, including diabetes, cardiovascular diseases, treatment of epilepsy and other debilitating neurological disorders. Despite extensive developments in sensing technologies, there are significant research issues related to system integration, sensor miniaturisation, low-power sensor interface, wireless telemetry and signal processing. In the 2nd edition of this popular and authoritative reference on Body Sensor Networks (BSN), major topics related to the latest technological developments and potential clinical applications are discussed, with contents covering. Biosensor Design, Interfacing and Nanotechnology Wireless Communication and Network Topologies Communication Protocols and Standards Energy Harvesting and Power Delivery Ultra-low Power Bio-inspired Processing Multi-sensor Fusion and Context Aware Sensing Autonomic Sensing Wearable, Ingestible Sensor Integration and Exemplar Applications System Integration and Wireless Sensor Microsystems The book also provides a comprehensive review of the current wireless sensor development platforms and a step-by-step guide to developing your own BSN applications through the use of the BSN development kit.