Moving Objects Detection Using Machine Learning
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| Author | : Navneet Ghedia |
| Publisher | : Springer Nature |
| Total Pages | : 91 |
| Release | : 2022-01-01 |
| Genre | : Technology & Engineering |
| ISBN | : 3030909107 |
This book shows how machine learning can detect moving objects in a digital video stream. The authors present different background subtraction approaches, foreground segmentation, and object tracking approaches to accomplish this. They also propose an algorithm that considers a multimodal background subtraction approach that can handle a dynamic background and different constraints. The authors show how the proposed algorithm is able to detect and track 2D & 3D objects in monocular sequences for both indoor and outdoor surveillance environments and at the same time, also able to work satisfactorily in a dynamic background and with challenging constraints. In addition, the shows how the proposed algorithm makes use of parameter optimization and adaptive threshold techniques as intrinsic improvements of the Gaussian Mixture Model. The presented system in the book is also able to handle partial occlusion during object detection and tracking. All the presented work and evaluations were carried out in offline processing with the computation done by a single laptop computer with MATLAB serving as software environment.
| Author | : Raut, Roshani |
| Publisher | : IGI Global |
| Total Pages | : 304 |
| Release | : 2021-01-29 |
| Genre | : Computers |
| ISBN | : 1799875172 |
Deep learning, as a recent AI technique, has proven itself efficient in solving many real-world problems. Deep learning algorithms are efficient, high performing, and an effective standard for solving these problems. In addition, with IoT, deep learning is in many emerging and developing domains of computer technology. Deep learning algorithms have brought a revolution in computer vision applications by introducing an efficient solution to several image processing-related problems that have long remained unresolved or moderately solved. Various significant IoT technologies in various industries, such as education, health, transportation, and security, combine IoT with deep learning for complex problem solving and the supported interaction between human beings and their surroundings. Examining the Impact of Deep Learning and IoT on Multi-Industry Applications provides insights on how deep learning, together with IoT, impacts various sectors such as healthcare, agriculture, cyber security, and social media analysis applications. The chapters present solutions to various real-world problems using these methods from various researchers’ points of view. While highlighting topics such as medical diagnosis, power consumption, livestock management, security, and social media analysis, this book is ideal for IT specialists, technologists, security analysts, medical practitioners, imaging specialists, diagnosticians, academicians, researchers, industrial experts, scientists, and undergraduate and postgraduate students who are working in the field of computer engineering, electronics, and electrical engineering.
| Author | : Soharab Hossain Shaikh |
| Publisher | : Springer |
| Total Pages | : 74 |
| Release | : 2014-06-20 |
| Genre | : Computers |
| ISBN | : 3319073869 |
This Springer Brief presents a comprehensive survey of the existing methodologies of background subtraction methods. It presents a framework for quantitative performance evaluation of different approaches and summarizes the public databases available for research purposes. This well-known methodology has applications in moving object detection from video captured with a stationery camera, separating foreground and background objects and object classification and recognition. The authors identify common challenges faced by researchers including gradual or sudden illumination change, dynamic backgrounds and shadow and ghost regions. This brief concludes with predictions on the future scope of the methods. Clear and concise, this brief equips readers to determine the most effective background subtraction method for a particular project. It is a useful resource for professionals and researchers working in this field.
| Author | : S Poonkuntran |
| Publisher | : CRC Press |
| Total Pages | : 345 |
| Release | : 2022-11-01 |
| Genre | : Computers |
| ISBN | : 1000686795 |
Object Detection with Deep Learning Models discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its applications to computer vision, illustrating them using key topics, including object detection, face analysis, 3D object recognition, and image retrieval. The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in deep learning, computer vision and beyond and can also be used as a reference book. The comprehensive comparison of various deep-learning applications helps readers with a basic understanding of machine learning and calculus grasp the theories and inspires applications in other computer vision tasks. Features: A structured overview of deep learning in object detection A diversified collection of applications of object detection using deep neural networks Emphasize agriculture and remote sensing domains Exclusive discussion on moving object detection
| Author | : Jason Brownlee |
| Publisher | : Machine Learning Mastery |
| Total Pages | : 564 |
| Release | : 2019-04-04 |
| Genre | : Computers |
| ISBN | : |
Step-by-step tutorials on deep learning neural networks for computer vision in python with Keras.
| Author | : Priyank Shah |
| Publisher | : GRIN Verlag |
| Total Pages | : 64 |
| Release | : 2014-06-16 |
| Genre | : Computers |
| ISBN | : 3656672660 |
Master's Thesis from the year 2014 in the subject Computer Science - Theory, grade: 9.2, , language: English, abstract: In this thesis we present an operational computer video system for moving object detection and tracking . The system captures monocular frames of background as well as moving object and to detect tracking and identifies those moving objects. An approach to statistically modeling of moving object developed using Background Subtraction Algorithms. There are many methods proposed for Background Subtraction algorithm in past years. Background subtraction algorithm is widely used for real time moving object detection in video surveillance system. In this paper we have studied and implemented different types of methods used for segmentation in Background subtraction algorithm with static camera. This paper gives good understanding about procedure to obtain foreground using existing common methods of Background Subtraction, their complexity, utility and also provide basics which will useful to improve performance in the future . First, we have explained the basic steps and procedure used in vision based moving object detection. Then, we have debriefed the common methods of background subtraction like Simple method, statistical methods like Mean and Median filter, Frame Differencing and W4 System method , Running Gaussian Average and Gaussian Mixture Model and last is Eigenbackground Model. After that we have implemented all the above techniques on MATLAB software and show some experimental results for the same and compare them in terms of speed and complexity criteria. Also we have improved one of the GMM algorithm by combining it with optical flow method, which is also good method to detect moving elements.
| Author | : Ashish Kumar |
| Publisher | : Springer Nature |
| Total Pages | : 280 |
| Release | : 2023-10-27 |
| Genre | : Computers |
| ISBN | : 9819932882 |
With the increase in urban population, it became necessary to keep track of the object of interest. In favor of SDGs for sustainable smart city, with the advancement in technology visual tracking extends to track multi-target present in the scene rather estimating location for single target only. In contrast to single object tracking, multi-target introduces one extra step of detection. Tracking multi-target includes detecting and categorizing the target into multiple classes in the first frame and provides each individual target an ID to keep its track in the subsequent frames of a video stream. One category of multi-target algorithms exploits global information to track the target of the detected target. On the other hand, some algorithms consider present and past information of the target to provide efficient tracking solutions. Apart from these, deep leaning-based algorithms provide reliable and accurate solutions. But, these algorithms are computationally slow when applied in real-time. This book presents and summarizes the various visual tracking algorithms and challenges in the domain. The various feature that can be extracted from the target and target saliency prediction is also covered. It explores a comprehensive analysis of the evolution from traditional methods to deep learning methods, from single object tracking to multi-target tracking. In addition, the application of visual tracking and the future of visual tracking can also be introduced to provide the future aspects in the domain to the reader. This book also discusses the advancement in the area with critical performance analysis of each proposed algorithm. This book will be formulated with intent to uncover the challenges and possibilities of efficient and effective tracking of single or multi-object, addressing the various environmental and hardware challenges. The intended audience includes academicians, engineers, postgraduate students, developers, professionals, military personals, scientists, data analysts, practitioners, and people who are interested in exploring more about tracking.· Another projected audience are the researchers and academicians who identify and develop methodologies, frameworks, tools, and applications through reference citations, literature reviews, quantitative/qualitative results, and discussions.
| Author | : Graeme A. Jones |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 277 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 1461509130 |
Monitoring of public and private sites has increasingly become a very sensitive issue resulting in a patchwork of privacy laws varying from country to country -though all aimed at protecting the privacy of the citizen. It is important to remember, however, that monitoring and vi sual surveillance capabilities can also be employed to aid the citizen. The focus of current development is primarily aimed at public and cor porate safety applications including the monitoring of railway stations, airports, and inaccessible or dangerous environments. Future research effort, however, has already targeted citizen-oriented applications such as monitoring assistants for the aged and infirm, route-planning and congestion-avoidance tools, and a range of environment al monitoring applications. The latest generation of surveillance systems has eagerly adopted re cent technological developments to produce a fully digital pipeline of digital image acquisition, digital data transmission and digital record ing. The resultant surveillance products are highly-fiexihle, capahle of generating forensic-quality imagery, and ahle to exploit existing Internet and wide area network services to provide remote monitoring capability.
| Author | : George A Tsihrintzis |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 633 |
| Release | : 2008-06-18 |
| Genre | : Mathematics |
| ISBN | : 3540681264 |
This book summarizes the works and new research results presented at the First International Symposium on Intelligent Interactive Multimedia Systems and Services (KES-IIMSS 2008), organized by the University of Piraeus and its Depa- ment of Informatics in conjunction with KES International (Piraeus, Greece, July 9–11, 2008). The aim of the symposium was to provide an internationally respected forum for scientific research into the technologies and applications of intelligent int- active multimedia systems and services. Besides the Preface, the book contains sixty four (64) chapters. The first four (4) chapters in the book are printed versions of the keynote addresses of the invited speakers of KES-IIMSS 2008. Besides the invited speaker chapters, the book contains fifteen (15) chapters on recent Advances in Multimedia Data Analysis, eleven (11) chapters on Reasoning Approaches, nine (9) chapters on Infrastructure of Intelligent Interactive Multimedia Systems and Services, fourteen (14) chapters on Multimedia Applications, and eleven (11) chapters on Quality of Interactive Multimedia Services.
| Author | : S R Boselin Prabhu |
| Publisher | : Educreation Publishing |
| Total Pages | : 71 |
| Release | : 2018-09-10 |
| Genre | : Education |
| ISBN | : |
Object tracking could be a terribly difficult task within the presence of variability illumination condition, background motion, complicated object form, partial and full object occlusions. The main intention of an object trailer is to make the path of an object over time by characteristic its position in all frames of the video. This book is intended to educate the researchers in the field of tracking of moving object(s) in a video sequence. This book provides a path for the researchers to identify the works done by others in the same field and thereby to figure out the gap in the current knowledge. This book is organized into three Modules. Module 1 talks about the introduction of object detection and tracking. Module 2 discusses about the various studies of object tracking and motion detection. The views of the various authors about this hot research topic are discussed in this Module and Module 3 gives the conclusion of the entire research review.Object tracking could be a terribly difficult task within the presence of variability illumination condition, background motion, complicated object form, partial and full object occlusions. The main intention of an object trailer is to make the path of an object over time by characteristic its position in all frames of the video. This book is intended to educate the researchers in the field of tracking of moving object(s) in a video sequence. This book provides a path for the researchers to identify the works done by others in the same field and thereby to figure out the gap in the current knowledge. This book is organized into three Modules. Module 1 talks about the introduction of object detection and tracking. Module 2 discusses about the various studies of object tracking and motion detection. The views of the various authors about this hot research topic are discussed in this Module and Module 3 gives the conclusion of the entire research review.
