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Object Detection by Stereo Vision Images

2022-09-14 Computers
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Release : 2022-09-14
Genre : Computers
Kind : eBook
Book Rating : 190/5 ( reviews)

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Book Synopsis Object Detection by Stereo Vision Images by : R. Arokia Priya

Download or read book Object Detection by Stereo Vision Images written by R. Arokia Priya. This book was released on 2022-09-14. Available in PDF, EPUB and Kindle. Book excerpt: OBJECT DETECTION BY STEREO VISION IMAGES Since both theoretical and practical aspects of the developments in this field of research are explored, including recent state-of-the-art technologies and research opportunities in the area of object detection, this book will act as a good reference for practitioners, students, and researchers. Current state-of-the-art technologies have opened up new opportunities in research in the areas of object detection and recognition of digital images and videos, robotics, neural networks, machine learning, stereo vision matching algorithms, soft computing, customer prediction, social media analysis, recommendation systems, and stereo vision. This book has been designed to provide directions for those interested in researching and developing intelligent applications to detect an object and estimate depth. In addition to focusing on the performance of the system using high-performance computing techniques, a technical overview of certain tools, languages, libraries, frameworks, and APIs for developing applications is also given. More specifically, detection using stereo vision images/video from its developmental stage up till today, its possible applications, and general research problems relating to it are covered. Also presented are techniques and algorithms that satisfy the peculiar needs of stereo vision images along with emerging research opportunities through analysis of modern techniques being applied to intelligent systems. Audience Researchers in information technology looking at robotics, deep learning, machine learning, big data analytics, neural networks, pattern & data mining, and image and object recognition. Industrial sectors include automotive electronics, security and surveillance systems, and online retailers.

Object Detection by Stereo Vision Images

2022-08-25 Computers
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Release : 2022-08-25
Genre : Computers
Kind : eBook
Book Rating : 263/5 ( reviews)

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Book Synopsis Object Detection by Stereo Vision Images by : R. Arokia Priya

Download or read book Object Detection by Stereo Vision Images written by R. Arokia Priya. This book was released on 2022-08-25. Available in PDF, EPUB and Kindle. Book excerpt: OBJECT DETECTION BY STEREO VISION IMAGES Since both theoretical and practical aspects of the developments in this field of research are explored, including recent state-of-the-art technologies and research opportunities in the area of object detection, this book will act as a good reference for practitioners, students, and researchers. Current state-of-the-art technologies have opened up new opportunities in research in the areas of object detection and recognition of digital images and videos, robotics, neural networks, machine learning, stereo vision matching algorithms, soft computing, customer prediction, social media analysis, recommendation systems, and stereo vision. This book has been designed to provide directions for those interested in researching and developing intelligent applications to detect an object and estimate depth. In addition to focusing on the performance of the system using high-performance computing techniques, a technical overview of certain tools, languages, libraries, frameworks, and APIs for developing applications is also given. More specifically, detection using stereo vision images/video from its developmental stage up till today, its possible applications, and general research problems relating to it are covered. Also presented are techniques and algorithms that satisfy the peculiar needs of stereo vision images along with emerging research opportunities through analysis of modern techniques being applied to intelligent systems. Audience Researchers in information technology looking at robotics, deep learning, machine learning, big data analytics, neural networks, pattern & data mining, and image and object recognition. Industrial sectors include automotive electronics, security and surveillance systems, and online retailers.

Combining Stereo Vision and Deep Learning Techniques for Object Detection in the 3D World

2020
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Release : 2020
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Kind : eBook
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Book Synopsis Combining Stereo Vision and Deep Learning Techniques for Object Detection in the 3D World by : Andrea Gimeno I Jovés

Download or read book Combining Stereo Vision and Deep Learning Techniques for Object Detection in the 3D World written by Andrea Gimeno I Jovés. This book was released on 2020. Available in PDF, EPUB and Kindle. Book excerpt: The objective of this project is to develop a deep learning algorithm so that, together with the use of a stereo camera, it is capable of detecting a person and locating them in the 3D world. The person's location in the x-y plane is obtained from the object detector model, which consists of a convolutional neural network, specifically the U-Net, that outputs heat maps. On the other hand, the person's location in terms of depth (z) is obtained from the depth map given by the ZED stereo camera. The document begins by presenting the techniques used today for object detection (using heat maps). This is followed by an explanation of the key theory behind neural networks; from the simplest neural networks to the convolutional neural networks. To finish with the theoretical part of the project, the hardware and software equipment used is presented. To develop and implement the deep learning algorithm, the first thing that is done is the dataset creation. In order to do that, different images have been selected and prepared to enter the network and train the model (using PyTorch) adapted to the needs of this task. Eight different combination of parameters have been used and eight different models have been obtained. Previously, the metric that will be used to evaluate and compare the different models obtained and choose the one that best suits this application, is defined. Once the final model is chosen, it is stored in the Jetson AGX Xavier and tested using ZED camera images. In this case, the model is verified to being accurate detecting people and the cases where the algorithm fails are identified. The next step of this project consists of applying stereo vision techniques to extract the distance at which the detected person is. A ROS node is created to communicate the ZED camera with the deep learning algorithm. Once the node is ready, it is executed to test the whole program in real time. The ZED color images are passed through the network to detect the person (x, y), and from the ZED depth map, the distance (z) is obtained. From the results obtained, both for the person detection and for the distance extraction, the existing errors in the designed algorithm are identified, and improvements are made by applying filters and code modifications. Thanks to the improvements applied to the results, a sufficient precise algorithm is obtained, capable of detecting a person within a distance range in real time.

Object Detection and Recognition in Digital Images

2013-05-20 Science
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Release : 2013-05-20
Genre : Science
Kind : eBook
Book Rating : 36X/5 ( reviews)

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Book Synopsis Object Detection and Recognition in Digital Images by : Boguslaw Cyganek

Download or read book Object Detection and Recognition in Digital Images written by Boguslaw Cyganek. This book was released on 2013-05-20. Available in PDF, EPUB and Kindle. Book excerpt: Object detection, tracking and recognition in images are key problems in computer vision. This book provides the reader with a balanced treatment between the theory and practice of selected methods in these areas to make the book accessible to a range of researchers, engineers, developers and postgraduate students working in computer vision and related fields. Key features: Explains the main theoretical ideas behind each method (which are augmented with a rigorous mathematical derivation of the formulas), their implementation (in C++) and demonstrated working in real applications. Places an emphasis on tensor and statistical based approaches within object detection and recognition. Provides an overview of image clustering and classification methods which includes subspace and kernel based processing, mean shift and Kalman filter, neural networks, and k-means methods. Contains numerous case study examples of mainly automotive applications. Includes a companion website hosting full C++ implementation, of topics presented in the book as a software library, and an accompanying manual to the software platform.

ACTIVE STEREO VISION: DEPTH PERCEPTION FOR NAVIGATION, ENVIRONMENTAL MAP FORMATION AND OBJECT RECOGNITION.

2003
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Release : 2003
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Book Synopsis ACTIVE STEREO VISION: DEPTH PERCEPTION FOR NAVIGATION, ENVIRONMENTAL MAP FORMATION AND OBJECT RECOGNITION. by :

Download or read book ACTIVE STEREO VISION: DEPTH PERCEPTION FOR NAVIGATION, ENVIRONMENTAL MAP FORMATION AND OBJECT RECOGNITION. written by . This book was released on 2003. Available in PDF, EPUB and Kindle. Book excerpt: In very few mobile robotic applications stereo vision based navigation and mapping is used because dealing with stereo images is very hard and very time consuming. Despite all the problems, stereo vision still becomes one of the most important resources of knowing the world for a mobile robot because imaging provides much more information than most other sensors. Real robotic applications are very complicated because besides the problems of finding how the robot should behave to complete the task at hand, the problems faced while controlling the robot’s internal parameters bring high computational load. Thus, finding the strategy to be followed in a simulated world and then applying this on real robot for real applications is preferable. In this study, we describe an algorithm for object recognition and cognitive map formation using stereo image data in a 3D virtual world where 3D objects and a robot with active stereo imaging system are simulated. Stereo imaging system is simulated so that the actual human visual system properties are parameterized. Only the stereo images obtained from this world are supplied to the virtual robot. By applying our disparity algorithm, depth map for the current stereo view is extracted. Using the depth information for the current view, a cognitive map of the environment is updated gradually while the virtual agent is exploring the environment. The agent explores its environment in an intelligent way using the current view and environmental map information obtained up to date. Also, during exploration if a new object is observed, the robot turns around it, obtains stereo images from different directions and extracts the model of the object in 3D. Using the available set of possible objects, it recognizes the object.

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