Results 31 to 40 of about 78,230 (294)
Neural RGB-D Surface Reconstruction
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 Obtaining high-quality 3D reconstructions of room-scale scenes is of paramount importance for upcoming applications in AR or VR. These range from mixed reality applications for teleconferencing, virtual measuring, virtual room planing, to robotic applications.
Azinovic, D. +4 more
openaire +3 more sources
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
doaj +1 more source
RGB-D datasets using microsoft kinect or similar sensors: a survey [PDF]
, 2015 RGB-D data has turned out to be a very useful representation of an indoor scene for solving fundamental computer vision problems. It takes the advantages of the color image that provides appearance information of an object and also the depth image that ...
Galili +7 more
core +2 more sources
RGB-D SLAM Combining Visual Odometry and Extended Information Filter
Sensors, 2015 In this paper, we present a novel RGB-D SLAM system based on visual odometry and an extended information filter, which does not require any other sensors or odometry.
Heng Zhang +3 more
doaj +1 more source
PL-GM:RGB-D SLAM With a Novel 2D and 3D Geometric Constraint Model of Point and Line Features
IEEE Access, 2021 In the study of RGB-D SLAM (Simultaneous Localization and Mapping), two types of primary visual features, point and line features, have been widely utilized to calculate the camera pose.
Chenyang Zhang
doaj +1 more source
Robust Intrinsic and Extrinsic Calibration of RGB-D Cameras [PDF]
, 2018 Color-depth cameras (RGB-D cameras) have become the primary sensors in most robotics systems, from service robotics to industrial robotics applications.
Basso, Filippo +2 more
core +2 more sources
Journal of Imaging, 2020 Depth sensors are important in several fields to recognize real space. However, there are cases where most depth values in a depth image captured by a sensor are constrained because the depths of distal objects are not always captured.
Naoyuki Awano
doaj +1 more source
Absolute and Relative Depth-Induced Network for RGB-D Salient Object Detection
Sensors, 2023 Detecting salient objects in complicated scenarios is a challenging problem. Except for semantic features from the RGB image, spatial information from the depth image also provides sufficient cues about the object.
Yuqiu Kong +5 more
doaj +1 more source
Low-Cost Three-Dimensional Modeling of Crop Plants
Sensors, 2019 Plant modeling can provide a more detailed overview regarding the basis of plant development throughout the life cycle. Three-dimensional processing algorithms are rapidly expanding in plant phenotyping programmes and in decision-making for agronomic ...
Jorge Martinez-Guanter +7 more
doaj +1 more source
Matterport3D: Learning from RGB-D Data in Indoor Environments
, 2017 Access to large, diverse RGB-D datasets is critical for training RGB-D scene understanding algorithms. However, existing datasets still cover only a limited number of views or a restricted scale of spaces.
Chang, Angel +8 more
core +1 more source