Results 51 to 60 of about 1,549,240 (256)
Motion Capture Research: 3D Human Pose Recovery Based on RGB Video Sequences
Applied Sciences, 2019 Using video sequences to restore 3D human poses is of great significance in the field of motion capture. This paper proposes a novel approach to estimate 3D human action via end-to-end learning of deep convolutional neural network to calculate the ...
Xin Min +5 more
doaj +1 more source
RGB-D people tracking by detection for a mobile robot [PDF]
, 2011 In this work, we propose a fast and robust multi-people long-term tracking algorithm for mobile platforms equipped with RGB-D sensors. The approach we followed is based on the clustering of the scene by using 3D information in conjunction with a reliable
Basso, Filippo
core
RGB-D video mirror detection [PDF]
Mirror detection aims to identify mirror areas in a scene, with recent methods either integrating depth information (RGB-D) or making use of temporal information (video).
Wu, Jing +4 more
core +1 more source
Advanced Robotics Research, EarlyView.This work presents a state‐adaptive Koopman linear quadratic regulator framework for real‐time manipulation of a deformable swab tool in robotic environmental sampling. By combining Koopman linearization, tactile sensing, and centroid‐based force regulation, the system maintains stable contact forces and high coverage across flat and inclined surfaces.
Siavash Mahmoudi +2 more
wiley +1 more source
Advanced Robotics Research, EarlyView.Here, we present a textile, wearable capacitive interface enabling multidirectional remote control by dynamically modulating electrode overlap and spacing via a freely gliding upper electrode. A forearm‐mounted prototype drives robotic and media tasks with 12–15 ms latency, maintains < 0.8% drift after 500 cycles, and remains stably functional at 90 ...
Cagatay Gumus +8 more
wiley +1 more source
Advanced Robotics Research, EarlyView.This work presents a robotic control method for human–robot collaborative assembly based on a biomechanics‐constrained digital human model. Reinforcement learning is used to generate physiologically plausible human motion trajectories, which are integrated into a virtual environment for robot control learning.
Bitao Yao +4 more
wiley +1 more source
MAC-REALM: A video content feature extraction and modelling framework [PDF]
, 2013 This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.A consequence of the ‘data deluge’ is the exponential increase in digital video footage, while the ability to find relevant video clips diminishes ...
Parmar, Minaz
core +5 more sources
Video Human Action Recognition Algorithm Based on Trained Image CNN Features [PDF]
Jisuanji gongcheng, 2017 In order to apply Convolutional Neural Network (CNN) to video understanding,a recognition algorithm based on trained image CNN features is proposed.Image RGB data is employed to recognize human action in videos.Off-the-shelf CNN models are used to ...
CAO Jinqi,JIANG Xinghao,SUN Tanfeng
doaj +1 more source
Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models
Advanced Robotics Research, EarlyView.A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki +2 more
wiley +1 more source
RGB Video- based 3D hand model control
, 2021 U ovom radu smo postigli upravljanje 3D modelom šake na temelju RGB videa. U prvom dijelu rada opisujemo sustav koji koristi algoritam za detekciju ljudske šake u RGB videu koristeći MediaPipe Hand Tracking te OpenCV biblioteke.
Krsmanović, Marko
core +3 more sources