Abstract
This paper presents a method for real-time detection and tracking of the human face. This is achieved using the Raspberry Pi microcomputer and the Easylab microcontroller as the main hardware with a camera mounted on servomotors for continuous image feed-in. Real-time face detection is performed using Haar-feature classifiers and ScicosLab in the Raspberry Pi. Then, the Easylab is responsible for face tracking, keeping the face in the middle of the frame through a pair of servomotors that control the horizontal and vertical movements of the camera. The servomotors are in turn controlled based on the state-diagrams designed using SMCube in the EasyLab. The methodology is verified via practical experimentation.
Original language | English |
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Title of host publication | Unknown Host Publication |
Publisher | IEEE |
Pages | 1-6 |
Number of pages | 6 |
ISBN (Electronic) | 978-1-5090-3549-6 |
ISBN (Print) | 978-1-5090-3549-6, 978-1-5090-4757-4 |
DOIs | |
Publication status | Published (in print/issue) - 2 Feb 2017 |
Event | 2016 14th International Conference on Control, Automation, Robotics & Vision Phuket, Thailand - Phuket, Thailand Duration: 2 Aug 2016 → … |
Conference
Conference | 2016 14th International Conference on Control, Automation, Robotics & Vision Phuket, Thailand |
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Period | 2/08/16 → … |
Keywords
- real-time
- face detection
- face tracking
- scicoslab
- smcube
- system-on-chip
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Mark Ng
- School of Engineering - Senior Lecturer
- Faculty Of Computing, Eng. & Built Env. - Senior Lecturer
Person: Academic