Adelaide Research & Scholarship
Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/83803
| Citations | ||
| Scopus | Web of Science® | Altmetric |
|---|---|---|
|
?
|
?
|
|
| Type: | Conference paper |
| Title: | Effective approaches in human action recognition |
| Author: | Li, X. Sheng, Q. Pang, C. Zhao, X. Wang, S. |
| Citation: | Proceedings of the 2013 IEEE Advanced Computer Science and Information Systems International Conference, ICACSIS 2013, 2013 / pp.1-7 |
| Publisher: | IEEE |
| Publisher Place: | USA |
| Issue Date: | 2013 |
| Series/Report no.: | International Conference on Advanced Computer Science and Information Systems-ICACSIS |
| ISBN: | 9789791421195 |
| ISSN: | 2330-4588 2473-7186 |
| Conference Name: | Advanced Computer Science and Information Systems International Conference (5th : 2013 : Bali, Indonesia) |
| Statement of Responsibility: | Xue Li, Quan Z. Sheng, Chaoyi Pang, Xin Zhao, and Sen Wang |
| Abstract: | Recognising and understanding the activities performed by people is a fundamental research topic in developing a wide range of applications that would be societally beneficial. In this article, we present and discuss two research projects on human action recognition based on computer vision techniques. We also report an ongoing research project that focuses on learning human activities through low cost, unobtrusive radio frequency identification (RFID) technology. |
| Rights: | ©2013 IEEE |
| DOI: | 10.1109/ICACSIS.2013.6761544 |
| Description (link): | http://icacsis.cs.ui.ac.id/index.php/icacsis2013/ICACSIS2013 |
| Published version: | http://dx.doi.org/10.1109/icacsis.2013.6761544 |
| Appears in Collections: | Aurora harvest Computer Science publications |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.