Project Title:
Android GPU Technology
Project Reference:
ART/170CP
Project Period:
20131223 - 20150622
Funds Approved (HK$’000):
14650
Project Coordinator:
Dr Jay Yeaun-Jau Liou
Deputy Project Coordinator:
/
Deliverable:
1. A highly efficient video/image processing middleware on an embedded CPU-GPU platform a) A high level video/image processing middleware framework for development of media application; and b) An OpenCL—compatible highly efficient video/image processing library that is reusable and scalable to different Android OS versions and different hardware platforms. 2. Reference design (both hardware and software) of the above mentioned middleware and demo applications such as object tracking and multi-window; and 3. One patent application in one of the below three areas: 1) Embedded Parallel sequential distributed computation methodology; 2) Object tracking algorithms. 3) Usability in the embedded multi-window environment
Research Group:
Mr Xiao Hao Lin
Mr Yee Lim Chan
Dr Yan Huo
Ms Lu Wang
Ms Yee Wai Mandy Yim
Mr Hanqiang Huang
Mr Pan Lit Wong
Mr Chi Chung Leung
Ms Hua Yang
Mr Fu Chun Li
Mr Kwok Hung Leung
Mr Yat Cheung Ngai
Ms Yin Yee Chan
Mr Sheng Zhou
Mr Ka Yuk Lee
Mr Chun Chung Lo
Mr Tony Wu
Mr RiHong Chen
Mr Denny Lai
Mr Teddy S. H. CHU
Mr Wong Tin Lung
Mr LaiFa Fang
Dr SaiFan, Dominic Chan
Mr QiangQi Zou
Mr William Wai Lun, Lee
Mr Ken Ka Fai Suk
Mr Edmund Ching Lun Lo
Mr Jeffrey Ding Lap Cheung
Mr Jackie Chi Hing Chau
Sponsor:
Aircraft Medical Ltd [Sponsor]
Clever Motion Technology Ltd (License Income) [Sponsor]
Hong Kong Linux Industry Association
KoolSee Medianet Corp Limited
KoolSee Medianet Corp Limited (License Income) [Sponsor]
Description:
Riding on the fast growing trend of low-cost, high-performance, multi-core Android SoC, this project aims to develop a video/image processing middleware technology platform for embedded systems(comparable to DirectX for PC) utilizing the heterogeneous CPU-GPU architecture of multi-core SoC. This technology will be hardware and Android version independent. It will provide unified APIs to application developers with rich video/image, camera and machine learning libraries extracted from academic research and ASTRI patent portfolio. It enables fast and efficient commercialization of academic/university research. Demo applications such as object tracking and multi-window will be developed in this project using the above mentioned middleware technology platform for proof-of-technology, innovative MMI applications, and early commercialization engagements.