scholarly journals Poster: Real time hand pose recognition with depth sensors for mixed reality interfaces

2013 ◽  
Author(s):  
Byungkyu Kang ◽  
Mathieu Rodrigue ◽  
Tobias Hollerer ◽  
Hwasup Lim
Keyword(s):  
Real Time ◽  
Mixed Reality ◽  
Pose Recognition ◽  
Depth Sensors ◽  
Hand Pose

Real-time, High-resolution Depth Upsampling on Embedded Accelerators

2021 ◽  
Vol 20 (3) ◽  
pp. 1-22
Author(s):  
David Langerman ◽  
Alan George
Keyword(s):  
High Resolution ◽  
Low Power ◽  
Real Time ◽  
Mixed Reality ◽  
Graphics Processing Unit ◽  
Processing Unit ◽  
Reconfigurable Logic ◽  
Depth Sensors ◽  
Time Requirements ◽  
Graphics Processing

High-resolution, low-latency apps in computer vision are ubiquitous in today’s world of mixed-reality devices. These innovations provide a platform that can leverage the improving technology of depth sensors and embedded accelerators to enable higher-resolution, lower-latency processing for 3D scenes using depth-upsampling algorithms. This research demonstrates that filter-based upsampling algorithms are feasible for mixed-reality apps using low-power hardware accelerators. The authors parallelized and evaluated a depth-upsampling algorithm on two different devices: a reconfigurable-logic FPGA embedded within a low-power SoC; and a fixed-logic embedded graphics processing unit. We demonstrate that both accelerators can meet the real-time requirements of 11 ms latency for mixed-reality apps. 1

FPVRGame: Deep Learning for Hand Pose Recognition in Real-Time Using Low-End HMD

2019 ◽  
pp. 70-84 ◽  
Author(s):  
Eder de Oliveira ◽  
Esteban Walter Gonzalez Clua ◽  
Cristina Nader Vasconcelos ◽  
Bruno Augusto Dorta Marques ◽  
Daniela Gorski Trevisan ◽  
...  
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Pose Recognition ◽  
Hand Pose

scholarly journals A Real-time Hand Pose Recognition Method with Hidden Finger Prediction

2012 ◽  
Vol 12 (5) ◽  
pp. 79-88 ◽  
Author(s):  
Min-Young Na ◽  
Jae-In Choi ◽  
Tae-Young Kim
Keyword(s):  
Real Time ◽  
Recognition Method ◽  
Pose Recognition ◽  
Hand Pose

Depth Data-Driven Real-Time Articulated Hand Pose Recognition

2014 ◽  
pp. 492-501
Author(s):  
Young-Woon Cha ◽  
Hwasup Lim ◽  
Min-Hyuk Sung ◽  
Sang Chul Ahn
Keyword(s):  
Real Time ◽  
Data Driven ◽  
Pose Recognition ◽  
Depth Data ◽  
Hand Pose

Real Time Hand Pose Estimation Using Depth Sensors

2013 ◽  
pp. 119-137 ◽  
Author(s):  
Cem Keskin ◽  
Furkan Kıraç ◽  
Yunus Emre Kara ◽  
Lale Akarun
Keyword(s):  
Real Time ◽  
Pose Estimation ◽  
Hand Pose Estimation ◽  
Depth Sensors ◽  
Hand Pose
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