This Conference Proceedings contains 58 papers presented in 8 sessions dealing with: vision and robotics problems needing solutions;pattern recognition for computervision;image processing;intelligent materials handli...
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This Conference Proceedings contains 58 papers presented in 8 sessions dealing with: vision and robotics problems needing solutions;pattern recognition for computervision;image processing;intelligent materials handling and vision;novel preprocessing algorithms and hardware;technology to support intelligentrobots and automated systems;fuzzy logic in intelligent systems and computervision;image segmentation techniques. The topics considered include the following, among others: learning procedure for the recognition of 3-D objects from 2-D images;flexible gray-level vision system based on multiple cell feature description and Hough transform;extraction of the foveal center and lesion boundary from fundus images;design and characterization of a space-variant CCD sensor;toward a general formula for analogical learning leading to more autonomous systems;image analysis using attributed fuzzy tournament matching algorithm;fuzzy logic for fault diagnosis;color segmentation using minimum description length (MDL) clustering;segmentation using range data and structured light;finding distinctive colored regions in images;multiresolution segmentation of forward-looking IP and SAR imagery using neural networks.
Existing studies on indoor position recognition employ diverse evaluation methods, which complicates direct accuracy comparisons across techniques. To address this issue, this study proposes a novel framework for eval...
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Existing studies on indoor position recognition employ diverse evaluation methods, which complicates direct accuracy comparisons across techniques. To address this issue, this study proposes a novel framework for evaluating the accuracy of indoor position recognition methods. The proposed framework evaluates accuracy by using the position recognition results of a grid-pattern-tracking autonomous mobile robot (GPT-AMR) as a benchmark. To validate the proposed evaluation method, a comparative analysis was conducted on four position recognition algorithms: (1) a computervision-based algorithm, (2) a Bluetooth Low Energy (BLE)-based trilateration algorithm, (3) a BLE-based adaptive trilateration algorithm, and (4) a least squares method (LSM)-based algorithm. Experimental results demonstrated that the proposed evaluation method, which employs GPT-AMR, offers improved speed, accuracy, and practical applicability compared to conventional approaches. Furthermore, this method enables objective comparisons and evaluations of a wide range of indoor position recognition technologies, including both computervision- and BLE-based algorithms, using a standardized criterion. Future research will focus on systematically validating the generalizability of the proposed method across different indoor environments and operational conditions. This study aims to advance indoor position recognition technology for autonomous mobile robots (AMRs) and improve their applicability in various service robotics domains.
Non-line-of-sight (NLOS) pedestrian detection is vital for uncovering hidden pedestrians and is crucial for autonomous driving and emergency response. Traditional methods depend on high-speed lasers and precise photon...
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ISBN:
(纸本)9789819786916;9789819786923
Non-line-of-sight (NLOS) pedestrian detection is vital for uncovering hidden pedestrians and is crucial for autonomous driving and emergency response. Traditional methods depend on high-speed lasers and precise photon detection devices, which are costly and complex. Aiming to streamline equipment and expand practicality, we explored using infrared cameras with object detection techniques on relay surfaces to detect hidden pedestrians. Despite the better reflectivity of infrared signals, such signals in the relay surface are too diffuse and vague for conventional pedestrian detection algorithms. To this end, our work introduces the Non-Lin-of-Sight Detection Net (NLOS-DetNet), which consists of a Hidden Object Enhancement Module (HOEM) to bolster relay surface features and a Hidden Object Detection Module (HODM), incorporating a Scattered Object Attention Module (SOAM) to utilize these enhanced signals for hidden pedestrian detection. With a custom long-wave infrared dataset for NLOS detection, our model pinpoints obscured pedestrians effectively and showcases the benefits of long-wave infrared for NLOS detection tasks.
Greenhouse vertical rack hydroponic systems offer a sustainable and efficient solution for meeting the increasing global food demand. This paper introduces an IoT-integrated automated system designed to perform labor ...
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The proceedings contain 38 papers from the Proceedings of SPIE: intelligentrobots and computervision XXII: algorithms, techniques, and Active vision. The topics discussed include: advances in learning for intelligen...
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The proceedings contain 38 papers from the Proceedings of SPIE: intelligentrobots and computervision XXII: algorithms, techniques, and Active vision. The topics discussed include: advances in learning for intelligent mobile robots;advanced remote operation of swarms of robots;a method for integrating vision and laser range measurements in autonomous ground robotic vehicles;calculation of the shortest-time path for traversal of an obstacle course by a robot;autonomous robot vision software design using Matlab toolboxes;visual terrain mapping for traversable path planning of mobile robots;segmentation algorithm for objects with very low edge contrast;and Bayesian stereo: 3D vision designed for sensor fusion.
The proceedings contains 53 papers from the SPIE Conference on intelligentrobots and computervision XVII: algorithms, techniques, and Active vision. Topics discussed include: planetary rovers for long-range Mars sci...
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The proceedings contains 53 papers from the SPIE Conference on intelligentrobots and computervision XVII: algorithms, techniques, and Active vision. Topics discussed include: planetary rovers for long-range Mars science and sample return;pose estimation;geometric and orthogonal moments;Shen-Castan and Canny-Deriche filters;Bayesian neural network learning;robot guidance;face recognition;wireless video monitoring and robot control;image processing for intelligent robotics;robot path planning, guidance and control;color computervision;3D visualization for intelligent robotics;active robotic vision;and image segmentation in computervision.
The proceedings contains 60 papers from the Proceedings of SPIE: intelligentrobots and computervision XX: algorithms, techniques, and Active vision. Topics discussed include: feature reduction methods for hyperspect...
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The proceedings contains 60 papers from the Proceedings of SPIE: intelligentrobots and computervision XX: algorithms, techniques, and Active vision. Topics discussed include: feature reduction methods for hyperspectral data;Bayesian object matching based on MCMC sampling and Gabor filters;Omnivision-based autonomous mobile robotic platform and case study of rotating sonar sensor application in unmanned automated guided vehicle.
The conference materials contain 71 papers. The main topics covered include pattern recognition in computervision;locating edges, lines curves, and surfaces in robotic vision;segmentation, motion, and color technique...
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ISBN:
(纸本)0819410268
The conference materials contain 71 papers. The main topics covered include pattern recognition in computervision;locating edges, lines curves, and surfaces in robotic vision;segmentation, motion, and color techniques;morphological processing for intelligent robotics;sensory robotics and control: vision, collision avoidance, path planning;visual servoing in automated manufacturing;and active vision.
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