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Visual Sensors

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Názov: Visual Sensors
Autori: Reinoso Garcia, Oscar, Payá, Luis
Informácie o vydavateľovi: MDPI - Multidisciplinary Digital Publishing Institute, 2020.
Rok vydania: 2020
Predmety: orientation relevance, sweet pepper, lane marking reconstruction, convolutional neural network, stereo-vision, single-shot 3D shape measurement, star image prediction, human visual system, support vector machines, motion estimation, patrol robot, mobile robots, iris recognition, motif co-occurrence histogram, advanced driver assistance system (ADAS), sign language, Gray code, appearance-temporal features, depth vision, fused point and line feature matching, robotics, FOV, image mosaic, visible light and near-infrared light camera sensors, illumination, indoor visual SLAM, textile localization, confidence response map, recognition algorithm, SLAM, inverse compositional Gauss-Newton algorithm, planes intersection, support vector machine (SVM), camera pose, TA1-2040, vibration, LSTM, camera calibration, iterative closest point, point cloud, appearance based model, statistical information of gray-levels differences, ego-motion estimation, catadioptric sensor, RGB-D sensor, warp function, texture description, image retrieval, texture retrieval, optical flow, action segmentation, visual odometry, thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology, automatic calibration, digital image correlation, 3D reconstruction, receptive field correspondence, visual detection, visual information fusion, Visual Sensors, semantic mapping, fringe projection profilometry, pedestrian detection, Siamese network, star sensor, visual tracking, lane marking, semantic segmentation, robot manipulation, n/a, end-to-end architecture, sensors combination, hybrid histogram descriptor, Richardson-Lucy algorithm, background dictionary, parallel line, rotation-angle, spatial transformation, human visual attention, scale invariance, action localization, indoor environment, robotic welding, speed measurement, depth image registration, Local Binary Patterns, laser sensor, stereo camera, image binarization, visual mapping, UAV image, underwater imaging, correlation filters, structure extraction, regression based model, dynamic programming, person re-identification, 3D ConvNets, convolutional neural network (CNN), geometric moments, pivotal frames, simplified initialization strategy, checkerboard, RGB-D, map representation, soft decision tree, stereo vision, CLOSIB, finger alphabet, large field of view, salient region detection, omnidirectional imaging, embedded systems, skeletal data, tightly-coupled VIO, Manhattan frame estimation, neural network, consistent line clustering, adaptive update strategy, textile retrieval, seam-line, pose estimation, lane marking detection, object recognition, vision system, presentation attack detection, content-based image retrieval, seam tracking, T1-995, vision-guided robotic grasping, quality control, automated design, GTAW, line scan camera, visual sensors, non-rigid reconstruction, stereo, adaptive model, extrinsic calibration, iris segmentation, calibration, symmetry axis, straight wing aircraft, image processing, around view monitor (AVM) system, motion-aware, handshape recognition, local parallel cross pattern, narrow butt joint, pose estimates, perceptually uniform histogram, LRF, visual sensor, visual localization, boosted decision tree, texture classification, parking assist system, global feature descriptor, measurement error, RGB-D SLAM
Popis: Visual sensors are able to capture a large quantity of information from the environment around them. A wide variety of visual systems can be found, from the classical monocular systems to omnidirectional, RGB-D, and more sophisticated 3D systems. Every configuration presents some specific characteristics that make them useful for solving different problems. Their range of applications is wide and varied, including robotics, industry, agriculture, quality control, visual inspection, surveillance, autonomous driving, and navigation aid systems. In this book, several problems that employ visual sensors are presented. Among them, we highlight visual SLAM, image retrieval, manipulation, calibration, object recognition, navigation, etc.
Druh dokumentu: Book
Popis súboru: application/octet-stream
Jazyk: English
Prístupová URL adresa: https://mdpi.com/books/pdfview/book/2141
https://directory.doabooks.org/handle/20.500.12854/62289
Rights: CC BY NC ND
Prístupové číslo: edsair.b80157a7a16b..3a20bf2a08dbb10c024c65fceadbf6c3
Databáza: OpenAIRE
Popis
Abstrakt:Visual sensors are able to capture a large quantity of information from the environment around them. A wide variety of visual systems can be found, from the classical monocular systems to omnidirectional, RGB-D, and more sophisticated 3D systems. Every configuration presents some specific characteristics that make them useful for solving different problems. Their range of applications is wide and varied, including robotics, industry, agriculture, quality control, visual inspection, surveillance, autonomous driving, and navigation aid systems. In this book, several problems that employ visual sensors are presented. Among them, we highlight visual SLAM, image retrieval, manipulation, calibration, object recognition, navigation, etc.