DSP-Based Facial Expression Recognition System
碩士 === 國立中山大學 === 電機工程學系研究所 === 93 === This thesis is based on the DSP to develop a facial expression recognition system. Most facial expression recognition systems suppose that human faces have been found, or the background colors are simple, or the facial feature points are extracted manually. Onl...
Main Authors: | , |
---|---|
Other Authors: | |
Format: | Others |
Language: | zh-TW |
Published: |
2005
|
Online Access: | http://ndltd.ncl.edu.tw/handle/91621154215297203654 |
id |
ndltd-TW-093NSYS5442037 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-TW-093NSYS54420372015-12-23T04:08:13Z http://ndltd.ncl.edu.tw/handle/91621154215297203654 DSP-Based Facial Expression Recognition System DSP-Based之臉部表情辨識系統 Chen-wei Hsu 徐晨暐 碩士 國立中山大學 電機工程學系研究所 93 This thesis is based on the DSP to develop a facial expression recognition system. Most facial expression recognition systems suppose that human faces have been found, or the background colors are simple, or the facial feature points are extracted manually. Only few recognition systems are automatic and complete. This thesis is a complete facial expression system. Images are captured by CCD camera. DSP locates the human face, extracts the facial feature points and recognizes the facial expression automatically. The recognition system is divided into four sub-system: Image capture system, Genetic Algorithm human face location system, Facial feature points extraction system, Fuzzy logic facial expression recognition system. Image capture system is using CCD camera to capture the facial expression image which will be recognized in any background, and transmitting the image data to SRAM on DSP through the PPI interface on DSP. Human face location system is using genetic algorithm to find the human face’s position in image by facial skin color and ellipse information, no matter what the size of the human face or the background is simple. Feature points extraction system is finding 16 facial feature points in located human face by many image process skills. Facial expression recognition system is analyzing facial action units by 16 feature points and making them fuzzily. Judging the four facial expression: happiness, anger, surprise and neutral, by fuzzy rule bases.. According to the results of the experiment. The facial expression system has nice performance on recognition rate and recognition speed. Tzuen-Lih Chern 陳遵立 2005 學位論文 ; thesis 79 zh-TW |
collection |
NDLTD |
language |
zh-TW |
format |
Others
|
sources |
NDLTD |
description |
碩士 === 國立中山大學 === 電機工程學系研究所 === 93 === This thesis is based on the DSP to develop a facial expression recognition system. Most facial expression recognition systems suppose that human faces have been found, or the background colors are simple, or the facial feature points are extracted manually. Only few recognition systems are automatic and complete. This thesis is a complete facial expression system. Images are captured by CCD camera. DSP locates the human face, extracts the facial feature points and recognizes the facial expression automatically.
The recognition system is divided into four sub-system: Image capture system, Genetic Algorithm human face location system, Facial feature points extraction system, Fuzzy logic facial expression recognition system. Image capture system is using CCD camera to capture the facial expression image which will be recognized in any background, and transmitting the image data to SRAM on DSP through the PPI interface on DSP. Human face location system is using genetic algorithm to find the human face’s position in image by facial skin color and ellipse information, no matter what the size of the human face or the background is simple. Feature points extraction system is finding 16 facial feature points in located human face by many image process skills. Facial expression recognition system is analyzing facial action units by 16 feature points and making them fuzzily. Judging the four facial expression: happiness, anger, surprise and neutral, by fuzzy rule bases..
According to the results of the experiment. The facial expression system has nice performance on recognition rate and recognition speed.
|
author2 |
Tzuen-Lih Chern |
author_facet |
Tzuen-Lih Chern Chen-wei Hsu 徐晨暐 |
author |
Chen-wei Hsu 徐晨暐 |
spellingShingle |
Chen-wei Hsu 徐晨暐 DSP-Based Facial Expression Recognition System |
author_sort |
Chen-wei Hsu |
title |
DSP-Based Facial Expression Recognition System |
title_short |
DSP-Based Facial Expression Recognition System |
title_full |
DSP-Based Facial Expression Recognition System |
title_fullStr |
DSP-Based Facial Expression Recognition System |
title_full_unstemmed |
DSP-Based Facial Expression Recognition System |
title_sort |
dsp-based facial expression recognition system |
publishDate |
2005 |
url |
http://ndltd.ncl.edu.tw/handle/91621154215297203654 |
work_keys_str_mv |
AT chenweihsu dspbasedfacialexpressionrecognitionsystem AT xúchénwěi dspbasedfacialexpressionrecognitionsystem AT chenweihsu dspbasedzhīliǎnbùbiǎoqíngbiànshíxìtǒng AT xúchénwěi dspbasedzhīliǎnbùbiǎoqíngbiànshíxìtǒng |
_version_ |
1718156092906668032 |