Visual Sensors

• Main Author: Reinoso Garcia, Oscar (auth)
• Other Authors: Payá, Luis (auth)
• Format: Electronic Book Chapter
• Language: English
• Published: MDPI - Multidisciplinary Digital Publishing Institute 2020
• Subjects: History of engineering & technology; recognition algorithm; n/a; 3D ConvNets; consistent line clustering; skeletal data; fused point and line feature matching; soft decision tree; texture retrieval; vision system; laser sensor; neural network; iris segmentation; correlation filters; embedded systems; underwater imaging; stereo vision; seam-line; image processing; quality control; dynamic programming; visual information fusion; semantic segmentation; parallel line; textile retrieval; structure extraction; line scan camera; orientation relevance; measurement error; rotation-angle; star image prediction; convolutional neural network (CNN); tightly-coupled VIO; visual sensors; stereo; parking assist system; visual detection; omnidirectional imaging; RGB-D SLAM; narrow butt joint; appearance-temporal features; vision-guided robotic grasping; scale invariance; support vector machine (SVM); straight wing aircraft; statistical information of gray-levels differences; Local Binary Patterns; robotics; mobile robots; textile localization; indoor environment; CLOSIB; geometric moments; perceptually uniform histogram; single-shot 3D shape measurement; salient region detection; person re-identification; calibration; stereo camera; simplified initialization strategy; LSTM; SLAM; image mosaic; convolutional neural network; lane marking detection; finger alphabet; robot manipulation; patrol robot; inverse compositional Gauss-Newton algorithm; checkerboard; action localization; hybrid histogram descriptor; pivotal frames; lane marking reconstruction; warp function; visual localization; RGB-D; automatic calibration; Siamese network; object recognition; human visual system; LRF; Gray code; visual tracking; motion-aware; visual odometry; adaptive update strategy; Manhattan frame estimation; vibration; confidence response map; lane marking; 3D reconstruction; indoor visual SLAM; pose estimation; global feature descriptor; sweet pepper; texture classification; ego-motion estimation; pose estimates; planes intersection; adaptive model; support vector machines; motif co-occurrence histogram; handshape recognition; non-rigid reconstruction; camera calibration; map representation; optical flow; robotic welding; FOV; background dictionary; appearance based model; Visual Sensors; spatial transformation; star sensor; image retrieval; depth vision; iterative closest point; automated design; semantic mapping; regression based model; seam tracking; image binarization; GTAW; boosted decision tree; pedestrian detection; presentation attack detection; visible light and near-infrared light camera sensors; large field of view; fringe projection profilometry; sensors combination; catadioptric sensor; RGB-D sensor; texture description; UAV image; motion estimation; extrinsic calibration; visual sensor; advanced driver assistance system (ADAS); content-based image retrieval; action segmentation; stereo-vision; visual mapping; around view monitor (AVM) system; illumination; speed measurement; Richardson-Lucy algorithm; digital image correlation; point cloud; receptive field correspondence; human visual attention; camera pose; sign language; symmetry axis; end-to-end architecture; local parallel cross pattern; iris recognition; depth image registration
• Online Access: DOAB: download the publication; DOAB: description of the publication

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.