Results 31 to 40 of about 64,265 (283)
Fusion in dissimilarity space for RGB-D person re-identification
Array, 2021 Person re-identification (Re-id) is the task of recognizing people across different non-overlapping sensors of a camera network. Despite the recent advances with deep learning (DL) models for multi-modal fusion, state-of-the-art Re-id approaches fail to ...
Md Kamal Uddin +4 more
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Applied Sciences, 2022 A novel method for structural health monitoring (SHM) by using RGB+D data has been recently proposed. RGB+D data are created by fusing image and laser scan data, where the D channel represents the distance, interpolated from laser scanner data.
Josip Peroš +3 more
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UNIPD-BPE: Synchronized RGB-D and Inertial Data for Multimodal Body Pose Estimation and Tracking
Data, 2022 The ability to estimate human motion without requiring any external on-body sensor or marker is of paramount importance in a variety of fields, ranging from human–robot interaction, Industry 4.0, surveillance, and telerehabilitation.
Mattia Guidolin +2 more
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SPLODE: Semi-Probabilistic Point and Line Odometry with Depth Estimation from RGB-D Camera Motion [PDF]
, 2017 Active depth cameras suffer from several limitations, which cause incomplete and noisy depth maps, and may consequently affect the performance of RGB-D Odometry.
Gao, Yang, Proença, Pedro F.
core +2 more sources
Non-Local Means Hole Repair Algorithm Based on Adaptive Block
Applied Sciences, 2023 RGB-D cameras provide depth and color information and are widely used in 3D reconstruction and computer vision. In the majority of existing RGB-D cameras, a considerable portion of depth values is often lost due to severe occlusion or limited camera ...
Bohu Zhao, Lebao Li, Haipeng Pan
doaj +1 more source
Soot volume fraction profiling of asymmetric diffusion flames through tomographic imaging [PDF]
, 2014 This paper presents the 3-D (three-dimensional) reconstruction of soot volume fraction of diffusion flames based on tomographic imaging and image processing techniques.
Hossain, Md. Moinul, Lu, Gang, Yan, Yong
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Data in Brief, 2019 This article contains data related to the research article entitle “Multi-modal Deep Learning for Fruit Detection Using RGB-D Cameras and their Radiometric Capabilities” [1].
Jordi Gené-Mola +5 more
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3D indoor scene modeling from RGB-D data: a survey [PDF]
, 2015 3D scene modeling has long been a fundamental problem in computer graphics and computer vision. With the popularity of consumer-level RGB-D cameras, there is a growing interest in digitizing real-world indoor 3D scenes. However, modeling indoor 3D scenes
Chen, Kang, Hu, Shi-Min, Lai, Yukun
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Analysis of Depth Cameras for Proximal Sensing of Grapes
Sensors, 2022 This work investigates the performance of five depth cameras in relation to their potential for grape yield estimation. The technologies used by these cameras include structured light (Kinect V1), active infrared stereoscopy (RealSense D415), time of ...
Baden Parr, Mathew Legg, Fakhrul Alam
doaj +1 more source
Indoor place categorization using co-occurrences of LBPs in gray and depth images from RGB-D sensors [PDF]
, 2014 Indoor place categorization is an important capability for service robots working and interacting in human environments. This paper presents a new place categorization method which uses information about the spatial correlation between the different ...
Iwashita, Yumi +3 more
core +1 more source