Download Drowsy Driver Detection Using Face Tracking Algorithms full books in PDF, epub, and Kindle. Read online Drowsy Driver Detection Using Face Tracking Algorithms ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Drowsy Driver Detection Using Face Tracking Algorithms by : Venkata Ravi Kiran Dayana
Download or read book Drowsy Driver Detection Using Face Tracking Algorithms written by Venkata Ravi Kiran Dayana and published by . This book was released on 2007 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt:
This book constitutes the refereed proceedings of the International Workshop on Human Computer Interaction, HCI 2007. Coverage in the 16 revised full papers presented includes affective detection and recognition, human motion tracking, multimedia data modeling and visualization, HCI issues in image/video retrieval, learning in HCI, input and interaction techniques, perceptual user interfaces, wearable and pervasive technologies in HCI and intelligent virtual environments.
Book Synopsis Human-Computer Interaction by : Michael Lew
Download or read book Human-Computer Interaction written by Michael Lew and published by Springer. This book was released on 2007-11-04 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the International Workshop on Human Computer Interaction, HCI 2007. Coverage in the 16 revised full papers presented includes affective detection and recognition, human motion tracking, multimedia data modeling and visualization, HCI issues in image/video retrieval, learning in HCI, input and interaction techniques, perceptual user interfaces, wearable and pervasive technologies in HCI and intelligent virtual environments.
Bachelor Thesis from the year 2019 in the subject Engineering - Robotics, grade: 78, University of Sunderland, language: English, abstract: This report explains the final project, driver drowsiness detection system. When a driver doesn’t get proper rest, they fall asleep while driving and this leads to fatal accidents. This particular issue demands a solution in the form of a system that is capable of detecting drowsiness and to take necessary actions to avoid accidents. The detection is achieved with three main steps, it begins with face detection and facial feature detection using the famous Viola Jones algorithm followed by eye tracking. By the use of correlation coefficient template matching, the eyes are tracked. Whether the driver is awake or asleep is identified by matching the extracted eye image with the externally fed template (open eyes and closed eyes) based on eyes opening and eyes closing, blinking is recognized. If the driver falling asleep state remains above a specific time (the threshold time) the vehicles stops and an alarm is activated by the use of a specific microcontroller, in this prototype an Arduino is used.
Book Synopsis Drowsiness Detection Using Image Processing by : Hanojhan Rajahrajasingh
Download or read book Drowsiness Detection Using Image Processing written by Hanojhan Rajahrajasingh and published by GRIN Verlag. This book was released on 2019-12-13 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bachelor Thesis from the year 2019 in the subject Engineering - Robotics, grade: 78, University of Sunderland, language: English, abstract: This report explains the final project, driver drowsiness detection system. When a driver doesn’t get proper rest, they fall asleep while driving and this leads to fatal accidents. This particular issue demands a solution in the form of a system that is capable of detecting drowsiness and to take necessary actions to avoid accidents. The detection is achieved with three main steps, it begins with face detection and facial feature detection using the famous Viola Jones algorithm followed by eye tracking. By the use of correlation coefficient template matching, the eyes are tracked. Whether the driver is awake or asleep is identified by matching the extracted eye image with the externally fed template (open eyes and closed eyes) based on eyes opening and eyes closing, blinking is recognized. If the driver falling asleep state remains above a specific time (the threshold time) the vehicles stops and an alarm is activated by the use of a specific microcontroller, in this prototype an Arduino is used.
This SpringerBrief presents the fundamentals of driver drowsiness detection systems, provides examples of existing products, and offers guides for practitioners interested in developing their own solutions to the problem. Driver drowsiness causes approximately 7% of all road accidents and up to 18% of fatal collisions. Proactive systems that are capable of preventing the loss of lives combine techniques, methods, and algorithms from many fields of engineering and computer science such as sensor design, image processing, computer vision, mobile application development, and machine learning which is covered in this brief. The major concepts addressed in this brief are: the need for such systems, the different methods by which drowsiness can be detected (and the associated terminology), existing commercial solutions, selected algorithms and research directions, and a collection of examples and case studies. These topics equip the reader to understand this critical field and its applications. Detection Systems and Solutions: Driver Drowsiness is an invaluable resource for researchers and professionals working in intelligent vehicle systems and technologies. Advanced-level students studying computer science and electrical engineering will also find the content helpful.
Book Synopsis Driver Drowsiness Detection by : Aleksandar Čolić
Download or read book Driver Drowsiness Detection written by Aleksandar Čolić and published by Springer. This book was released on 2014-09-27 with total page 57 pages. Available in PDF, EPUB and Kindle. Book excerpt: This SpringerBrief presents the fundamentals of driver drowsiness detection systems, provides examples of existing products, and offers guides for practitioners interested in developing their own solutions to the problem. Driver drowsiness causes approximately 7% of all road accidents and up to 18% of fatal collisions. Proactive systems that are capable of preventing the loss of lives combine techniques, methods, and algorithms from many fields of engineering and computer science such as sensor design, image processing, computer vision, mobile application development, and machine learning which is covered in this brief. The major concepts addressed in this brief are: the need for such systems, the different methods by which drowsiness can be detected (and the associated terminology), existing commercial solutions, selected algorithms and research directions, and a collection of examples and case studies. These topics equip the reader to understand this critical field and its applications. Detection Systems and Solutions: Driver Drowsiness is an invaluable resource for researchers and professionals working in intelligent vehicle systems and technologies. Advanced-level students studying computer science and electrical engineering will also find the content helpful.
This conference covers the joint areas of pattern recognition, artificial intelligence, robotics and mechatronics
Book Synopsis 2017 Pattern Recognition Association of South Africa and Robotics and Mechatronics (PRASA RobMech) by : IEEE Staff
Download or read book 2017 Pattern Recognition Association of South Africa and Robotics and Mechatronics (PRASA RobMech) written by IEEE Staff and published by . This book was released on 2017-11-30 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This conference covers the joint areas of pattern recognition, artificial intelligence, robotics and mechatronics
This study involved the collection of real-world driving data from a small sample of drivers, thought to be at heightened risk, to identify periods of drowsiness and inattention. Data included a variety of engineering measures including video of the driver and the road scene. One objective of the study was the identification of periods of drowsiness and inattention, documented on video, that would be made available for public education and outreach programs. A second objective was to validate, in a naturalistic driving setting, the drowsy driver detection algorithms developed by Wierwille, et al. in a simulator environment. Participants' personal vehicles were instrumented with the MicroDAS instrumentation system and all driving during the data collection was fully discretionary and independent of study objectives. The study thus offered the opportunity to implement highly unobtrusive data collection in subjects own vehicles with the absence of an experimenter in an effort to gather naturalistic data with a minimum of experimental artifacts. Results highlight the importance of lanekeeping variation as a key predictor variable for detecting drowsiness while driving, although the drowsy detection algorithm did not perform as well as in the simulator studies. An attempt to relate algorithm results to the prediction of driver inattention was inconclusive. The results are discussed in terms of theoretical, and procedural issues associated with inattention, drowsiness and driver responses to false positive epochs. It is suggested that the use of a multiplicity of approaches for addressing drowsy and inattentive driving would be most effective, and recommendations are made for future research on both technological and behavioral interventions
Book Synopsis A Preliminary Assessment of Algorithms for Drowsy and Inattentive Driver Detection on the Road by : Louis Tijerina
Download or read book A Preliminary Assessment of Algorithms for Drowsy and Inattentive Driver Detection on the Road written by Louis Tijerina and published by . This book was released on 1998 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study involved the collection of real-world driving data from a small sample of drivers, thought to be at heightened risk, to identify periods of drowsiness and inattention. Data included a variety of engineering measures including video of the driver and the road scene. One objective of the study was the identification of periods of drowsiness and inattention, documented on video, that would be made available for public education and outreach programs. A second objective was to validate, in a naturalistic driving setting, the drowsy driver detection algorithms developed by Wierwille, et al. in a simulator environment. Participants' personal vehicles were instrumented with the MicroDAS instrumentation system and all driving during the data collection was fully discretionary and independent of study objectives. The study thus offered the opportunity to implement highly unobtrusive data collection in subjects own vehicles with the absence of an experimenter in an effort to gather naturalistic data with a minimum of experimental artifacts. Results highlight the importance of lanekeeping variation as a key predictor variable for detecting drowsiness while driving, although the drowsy detection algorithm did not perform as well as in the simulator studies. An attempt to relate algorithm results to the prediction of driver inattention was inconclusive. The results are discussed in terms of theoretical, and procedural issues associated with inattention, drowsiness and driver responses to false positive epochs. It is suggested that the use of a multiplicity of approaches for addressing drowsy and inattentive driving would be most effective, and recommendations are made for future research on both technological and behavioral interventions
This book constitutes the proceedings of the Third Workshop on Face and Facial Expression Recognition from Real World Videos, FFER 2018, and the Second International Workshop on Deep Learning for Pattern Recognition, DLPR 2018, held at the 24th International Conference on Pattern Recognition, ICPR 2018, in Beijing, China, in August 2018. The 7 papers presented in this volume were carefully reviewed and selected from 9 submissions. They deal with topics such as histopathological images, action recognition, scene text detection, speech recognition, object classification, presentation attack detection, and driver drowsiness detection.
Book Synopsis Video Analytics. Face and Facial Expression Recognition by : Xiang Bai
Download or read book Video Analytics. Face and Facial Expression Recognition written by Xiang Bai and published by Springer. This book was released on 2019-01-18 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the Third Workshop on Face and Facial Expression Recognition from Real World Videos, FFER 2018, and the Second International Workshop on Deep Learning for Pattern Recognition, DLPR 2018, held at the 24th International Conference on Pattern Recognition, ICPR 2018, in Beijing, China, in August 2018. The 7 papers presented in this volume were carefully reviewed and selected from 9 submissions. They deal with topics such as histopathological images, action recognition, scene text detection, speech recognition, object classification, presentation attack detection, and driver drowsiness detection.
This book consists of papers on the recent progresses in the state of the art in natural computation, fuzzy systems, and knowledge discovery. The book is useful for researchers, including professors, graduate students, as well as R & D staff in the industry, with a general interest in natural computation, fuzzy systems, and knowledge discovery. The work printed in this book was presented at the 2022 18th International Conference on Natural Computation, Fuzzy Systems, and Knowledge Discovery (ICNC-FSKD 2022), held from 30 July to 1 August 2022, in Fuzhou, China. All papers were rigorously peer-reviewed by experts in the areas.
Book Synopsis Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery by : Ning Xiong
Download or read book Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery written by Ning Xiong and published by Springer Nature. This book was released on 2023-01-29 with total page 1527 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book consists of papers on the recent progresses in the state of the art in natural computation, fuzzy systems, and knowledge discovery. The book is useful for researchers, including professors, graduate students, as well as R & D staff in the industry, with a general interest in natural computation, fuzzy systems, and knowledge discovery. The work printed in this book was presented at the 2022 18th International Conference on Natural Computation, Fuzzy Systems, and Knowledge Discovery (ICNC-FSKD 2022), held from 30 July to 1 August 2022, in Fuzhou, China. All papers were rigorously peer-reviewed by experts in the areas.
Book Synopsis Smart Data Intelligence by : R. Asokan
Download or read book Smart Data Intelligence written by R. Asokan and published by Springer Nature. This book was released on with total page 668 pages. Available in PDF, EPUB and Kindle. Book excerpt:
This volume presents a collection of peer-reviewed, scientific articles from the 15th International Conference on Information Technology – New Generations, held at Las Vegas. The collection addresses critical areas of Machine Learning, Networking and Wireless Communications, Cybersecurity, Data Mining, Software Engineering, High Performance Computing Architectures, Computer Vision, Health, Bioinformatics, and Education.
Book Synopsis Information Technology - New Generations by : Shahram Latifi
Download or read book Information Technology - New Generations written by Shahram Latifi and published by Springer. This book was released on 2018-04-12 with total page 818 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents a collection of peer-reviewed, scientific articles from the 15th International Conference on Information Technology – New Generations, held at Las Vegas. The collection addresses critical areas of Machine Learning, Networking and Wireless Communications, Cybersecurity, Data Mining, Software Engineering, High Performance Computing Architectures, Computer Vision, Health, Bioinformatics, and Education.