Search
Publication Authors

Prof. Dr. Didier Stricker

Dr. Alain Pagani

Dr. Gerd Reis

Eric Thil

Keonna Cunningham

Monika Miersch

Dr. Oliver Wasenmüller

Dr. Muhammad Zeshan Afzal

Dr. Gabriele Bleser

Dr. Muhammad Jameel Nawaz Malik

Dr. Bruno Mirbach

Dr. Jason Raphael Rambach

Dr. Nadia Robertini

Dr. René Schuster

Dr. Bertram Taetz

Ahmed Aboukhadra

Sk Aziz Ali

Mhd Rashed Al Koutayni

Yuriy Anisimov

Muhammad Asad Ali

Jilliam Maria Diaz Barros

Ramy Battrawy
Katharina Bendig
Hammad Butt

Mahdi Chamseddine
Chun-Peng Chang
Steve Dias da Cruz
Fangwen Shu

Torben Fetzer

Ahmet Firintepe

Sophie Folawiyo

David Michael Fürst
Anshu Garg

Christiano Couto Gava
Suresh Guttikonda

Tewodros Amberbir Habtegebrial

Simon Häring

Khurram Azeem Hashmi

Dr. Anna Katharina Hebborn

Hamoun Heidarshenas
Henri Hoyez

Pragati Jaiswal

Alireza Javanmardi
M.Sc. Sai Srinivas Jeevanandam

Jigyasa Singh Katrolia

Matin Keshmiri

Andreas Kölsch
Ganesh Shrinivas Koparde
Onorina Kovalenko

Stephan Krauß
Paul Lesur

Michael Lorenz

Dr. Markus Miezal

Mina Ameli

Nareg Minaskan Karabid

Mohammad Minouei

Shashank Mishra

Pramod Murthy

Mathias Musahl
Peter Neigel

Manthan Pancholi

Mariia Podguzova

Praveen Nathan
Qinzhuan Qian
Rishav

Marcel Rogge
María Alejandra Sánchez Marín
Dr. Kripasindhu Sarkar

Alexander Schäfer

Pascal Schneider

Dr. Mohamed Selim

Tahira Shehzadi
Lukas Stefan Staecker

Yongzhi Su

Xiaoying Tan

Shaoxiang Wang
Christian Witte

Yaxu Xie

Vemburaj Yadav

Yu Zhou

Dr. Vladislav Golyanik

Dr. Aditya Tewari

André Luiz Brandão
Publication Archive
New title
- ActivityPlus
- AlterEgo
- AR-Handbook
- ARVIDA
- Auroras
- AVILUSplus
- Be-greifen
- Body Analyzer
- CAPTURE
- Co2Team
- COGNITO
- DAKARA
- Density
- DYNAMICS
- EASY-IMP
- ENNOS
- Eyes Of Things
- iACT
- IMCVO
- IVMT
- LARA
- LiSA
- Marmorbild
- Micro-Dress
- Odysseus Studio
- On Eye
- OrcaM
- PAMAP
- PROWILAN
- ServiceFactory
- STREET3D
- SUDPLAN
- SwarmTrack
- TuBUs-Pro
- VIDETE
- VIDP
- VisIMon
- VISTRA
- VIZTA
- You in 3D
Real-Time Energy Efficient Hand Pose Estimation: A Case Study
Real-Time Energy Efficient Hand Pose Estimation: A Case Study
Mhd Rashed Al Koutayni, Vladimir Rybalkin, Muhammad Jameel Nawaz Malik, Ahmed Elhayek, Christian Weis, Gerd Reis, Norbert Wehn, Didier Stricker
Sensors - Open Access Journal (sensors) 20 Seiten 1-27 MDPI 5/2020 .
- Abstract:
- The estimation of human hand pose has become the basis for many vital applications where the user depends mainly on the hand pose as a system input. Virtual reality (VR) headset, shadow dexterous hand and in-air signature verification are a few examples of applications that require to track the hand movements in real-time. The state-of-the-art 3D hand pose estimation methods are based on the Convolutional Neural Network (CNN). These methods are implemented on Graphics Processing Units (GPUs) mainly due to their extensive computational requirements. However, GPUs are not suitable for the practical application scenarios, where the low power consumption is crucial. Furthermore, the difficulty of embedding a bulky GPU into a small device prevents the portability of such applications on mobile devices. The goal of this work is to provide an energy efficient solution for an existing depth camera based hand pose estimation algorithm. First, we compress the deep neural network model by applying the dynamic quantization techniques on different layers to achieve maximum compression without compromising accuracy. Afterwards, we design a custom hardware architecture. For our device we selected the FPGA as a target platform because FPGAs provide high energy efficiency and can be integrated in portable devices. Our solution implemented on Xilinx UltraScale+ MPSoC FPGA is 4.2x faster and 577.3x more energy efficient than the original implementation of the hand pose estimation algorithm on NVIDIA GeForce GTX 1070.