Real-time face detection and tracking using software and hardware design
| dc.contributor.author | Chen, Kok Keat | |
| dc.date.accessioned | 2021-04-15T06:16:01Z | |
| dc.date.available | 2021-04-15T06:16:01Z | |
| dc.date.issued | 2018-06 | |
| dc.description.abstract | This project presents the design and the implementation of face detection algorithm for video processing applications on FPGAs. Face detection and tracking has been an active research topic because it offers many important applications, especially in video surveillance, biometrics, video coding and so on. The goal of this project was to implement a real-time system on an FPGA to detect and track human faces. The face detection algorithm involved colour-based skin segmentation and image filtering. The face location was determined by calculating the centroid of the detected region. A software version of the algorithm was independently implemented and tested in MATLAB Simulink. Although the transition from software version to HDL (Verilog) was not exactly the same between both approaches, experimental results proved the functionality, accuracy and effectiveness of the real-time system, even under varying conditions of lights, facial poses and skin colours. For FPGA implementation the entire face detection algorithm was implemented on Cyclone IV FPGA device using Altera DE2-115. The input video or image came from a Terasic Capacitive Multi-Touch LCD with Camera Module (MTLC) and the outputs were displayed on a VGA monitor. All calculations of the hardware implementation were done in real time with minimal computational effort, thus suitable for power-limited applications. | en_US |
| dc.identifier.uri | http://hdl.handle.net/123456789/12870 | |
| dc.language.iso | en | en_US |
| dc.title | Real-time face detection and tracking using software and hardware design | en_US |
| dc.type | Other | en_US |
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