Zlepšení metod rozpoznávání obličejů s pomocí senzoru pro sledování pohybu těla
| Thesis title in Czech: | Zlepšení metod rozpoznávání obličejů s pomocí senzoru pro sledování pohybu těla |
|---|---|
| Thesis title in English: | Improving Face Recognition Methods with Body Tracking Sensor |
| Academic year of topic announcement: | 2017/2018 |
| Thesis type: | Bachelor's thesis |
| Thesis language: | angličtina |
| Department: | Department of Software Engineering (32-KSI) |
| Supervisor: | doc. RNDr. Martin Kruliš, Ph.D. |
| Author: | hidden - assigned and confirmed by the Study Dept. |
| Date of registration: | 09.04.2018 |
| Date of assignment: | 10.04.2018 |
| Confirmed by Study dept. on: | 23.04.2018 |
| Date and time of defence: | 06.09.2018 09:00 |
| Date of electronic submission: | 20.07.2018 |
| Date of submission of printed version: | 20.07.2018 |
| Date of proceeded defence: | 06.09.2018 |
| Opponents: | doc. RNDr. Jakub Lokoč, Ph.D. |
| Guidelines |
| Kinect is a motion tracking input device developed by Microsoft. It uses a variety of on-board sensors to efficiently find and track human bodies represented in skeletal models. It was developed primarily to facilitate control of the Xbox 360 gaming console using body movement. Microsoft also released an SDK for Kinect, giving programmers access to both raw data streams and computed tracking data from a connected Kinect. A second version of Kinect was released for Xbox One, bringing various hardware improvements as well as a new and incompatible version of the SDK.
The main objective of this thesis is to determine, whether Kinect may be a better platform for real-time face tracking than regular cameras. A software compatible with both versions of Kinect will be developed that will combine Kinect tracking data with existing face recognition libraries. The software will be used to assess the benefits of tracking data by empirical evalution on collected data. |
| References |
| Knoop, Steffen, Stefan Vacek, and Rüdiger Dillmann. "Sensor fusion for 3D human body tracking with an articulated 3D body model." Robotics and Automation, 2006. ICRA 2006. Proceedings 2006 IEEE International Conference on. IEEE, 2006.
Azarbayejani, Ali, Christopher Wren, and Alex Pentland. "Real-time 3-D tracking of the human body." IMAGE'COM, Bordeaux, France (1996). Jain, Anil K., and Stan Z. Li. Handbook of face recognition. New York: springer, 2011. |