Results 41 to 50 of about 21,157 (187)
XNect: Real-time Multi-Person 3D Motion Capture with a Single RGB Camera
, 2020 We present a real-time approach for multi-person 3D motion capture at over 30 fps using a single RGB camera. It operates successfully in generic scenes which may contain occlusions by objects and by other people. Our method operates in subsequent stages.
Elgharib, Mohamed +9 more
core +1 more source
Pseudo-LiDAR With Two-Dimensional Instance for Monocular Three-Dimensional Object Tracking
IEEE AccessEstablishing a framework capable of performing 3D object tracking is crucial for various applications, such as autonomous driving and robot navigation. Monocular cameras offer economic and flexible advantages over LiDAR sensors; however, monocular camera-
Rui Gao +3 more
doaj +1 more source
Probabilistic Global Scale Estimation for MonoSLAM Based on Generic Object Detection
, 2017 This paper proposes a novel method to estimate the global scale of a 3D reconstructed model within a Kalman filtering-based monocular SLAM algorithm. Our Bayesian framework integrates height priors over the detected objects belonging to a set of broad ...
Hayet, Jean-Bernard, Sucar, Edgar
core +1 more source
Mono3D++: Monocular 3D Vehicle Detection with Two-Scale 3D Hypotheses and Task Priors
, 2019 We present a method to infer 3D pose and shape of vehicles from a single image. To tackle this ill-posed problem, we optimize two-scale projection consistency between the generated 3D hypotheses and their 2D pseudo-measurements.
He, Tong, Soatto, Stefano
core +1 more source
Frontiers in Computer ScienceAutonomous driving is the future trend. Accurate 3D object detection is a prerequisite for achieving autonomous driving. Currently, 3D object detection relies on three main sensors: monocular cameras, stereo cameras, and lidar.
Yanfei Gao, Xiongwei Miao, Guoye Zhang
doaj +1 more source
Object-Aware Centroid Voting for Monocular 3D Object Detection [PDF]
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020 Monocular 3D object detection aims to detect objects in a 3D physical world from a single camera. However, recent approaches either rely on expensive LiDAR devices, or resort to dense pixel-wise depth estimation that causes prohibitive computational cost.
Bao, Wentao, Yu, Qi, Kong, Yu
openaire +2 more sources
2D Instance-Guided Pseudo-LiDAR Point Cloud for Monocular 3D Object Detection
IEEE AccessMonocular three-dimensional (3D) scene understanding tasks, e.g., object size angle and 3D position, estimation are challenging to perform. More successful current methods usually require data from 3D sensors, which limits their performance if only ...
Rui Gao, Junoh Kim, Kyungeun Cho
doaj +1 more source
Geometry-Aware Network for Non-Rigid Shape Prediction from a Single View [PDF]
, 2018 We propose a method for predicting the 3D shape of a deformable surface from a single view. By contrast with previous approaches, we do not need a pre-registered template of the surface, and our method is robust to the lack of texture and partial ...
Agudo, Antonio +5 more
core +2 more sources
MonoMPV: Monocular 3D Object Detection With Multiple Projection Views on Edge Devices
IEEE AccessIn the field of autonomous driving, monocular 3D object detection is focused on the task of representing 3D scenes using a single camera image and conducting 3D object detection.
Zhaoxue Deng +6 more
doaj +1 more source
Fast, Accurate Thin-Structure Obstacle Detection for Autonomous Mobile Robots
, 2017 Safety is paramount for mobile robotic platforms such as self-driving cars and unmanned aerial vehicles. This work is devoted to a task that is indispensable for safety yet was largely overlooked in the past -- detecting obstacles that are of very thin ...
Hua, Gang +3 more
core +1 more source