即時人臉偵測、姿態辨識與追蹤系統實現於複雜環境

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姓名

梁守鈞(Shou-jyun Liang) 查詢紙本館藏

畢業系所

電機工程學系

論文名稱

即時人臉偵測、姿態辨識與追蹤系統實現於複雜環境
(Real Time Human Face Detection, Posture Recognition and Tracking System Realized in Complex Environment)

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摘要(中)

本文旨在實現人臉偵測、辨識人臉姿態與追蹤於即時動態影像，透過攝影機擷取影像，首先利用閥值把膚色與影像分離，經過形態學處理，把不必要的雜訊給移除，最後使用種子區域生長法，標記每個膚色的區塊，使用人臉判定法，假如膚色區塊不是人臉的話就被捨去掉。
當人臉被偵測出來，使用小波圖像分割法，抓取低頻子影像去做辨識，使用二維主成份分析(2DPCA)演算法去做辨識，辨識結果為側臉就不進行追蹤，只有辨識為正臉才進行追蹤。
當正臉被辨識成功，找出中心點的位置，對人臉建構顏色直方圖模型，人臉追蹤演算法是使用自組織隨時調變係數的粒子最佳化 (HPSO-TVAC) 演算法，當人臉遇到遮蔽問題，本文使用自適應搜尋框，當找不到人臉時使用較大的搜尋框，搜尋框的縮放是依照群體最佳適應值。

摘要(英)

The main purposes of this thesis are to achieve human face detection and head posture recognition, as well as to track a dynamic image in real time via camera. First, skin-color region is detected, after morphological operations, unnecessary noise is removed, and the method of seed region growing is used to mark pixel blocks. Then the skin-color region is determined whether or not each block is a human face. If it is not human face, it is discarded. Otherwise, wavelet transform is used to decompose the face image. A low-frequency sub-band face image is captured by wavelet transform, and two-dimensional principle component analysis (2DPCA) is used to recognize head posture. Face color histograms are used to build face models, and faces are traced by the Self-Organizing Hierarchical Particle Swarm Optimizer With Time-Varying Acceleration Coefficients (HPSO-TVAC) algorithm. In order to solve the face masking problem, adaptive seeking windows are applied. When a human face is not detected, a large seeking window will be used, which will zoom in or out depending on the best global fitness.

關鍵字(中)

★ 人臉偵測
★ 種子區域生長法
★ 小波圖像分割法
★ 2DPCA演算法
★ HPSO-TVAC演算法
★ 自適應搜尋框

關鍵字(英)

★ Face Detecting
★ Seed Region Growing
★ Wavelet Transform
★ 2DPCA
★ HPSO-TVAC
★ Adaptive Seeking Window

論文目次

目錄
頁次
中文摘要 i
英文摘要 ii
誌謝 iii
目錄 iv
圖目錄 vii
表目錄 x
第一章緒論 1
1-1 簡介 1
1-2 研究動機與方法 2
1-3 文獻回顧與探討 3
1-4 主要貢獻 4
1-5 論文架構 5
第二章軟硬體與系統模型 6
2-1 外部硬體 6
2-2 內部軟體 7
2-3 系統架構 9
第三章人臉偵測 10
3-1 色彩空間介紹 11
3-1-1 RGB色彩空間 11
3-1-2 Lab色彩空間 12
3-1-3 YIQ色彩空間 12
3-1-4 YCbCr色彩空間 12
3-1-5 HSV色彩空間 13
3-2 膚色切割法 14
3-3 二值化處理 16
3-4 形態學處理 17
3-4-1 侵蝕(Erosion) 17
3-4-2 膨脹(Dilation) 19
3-4-3 斷開(Opening) 20
3-4-4 閉合(Closing) 21
3-4-5 雜訊移除(Noise Removal) 22
3-5 連通區域標記法 24
3-5-1 區域分裂合併法(Region Splitting and Merging) 24
3-5-2 分水嶺法(Watershed) 25
3-5-3 種子區域生長法(Seeded Region Growing) 26
3-5-4 改良式種子區域生長法 28
3-6 人臉判定法 32
3-6-1 人臉的長寬比例 32
3-6-2 臉部的黑洞數 32
第四章人臉姿態辨識 35
4-1 雙線性內插縮圖法 36
4-2 小波圖像分割法 38
4-2-1 小波介紹 38
4-2-2 小波應用於影像辨識 38
4-3 主成份分析演算法 41
4-3-1 主成份分析簡介 41
4-3-2 主成份分析應用於影像辨識 42
4-4 二維主成份分析演算法 46
4-5 辨識方法 51
第五章人臉追蹤方法與分析 52
5-1 建構人臉直方圖模型 53
5-2 基本PSO演算法 56
5-3 HPSO-TVAC演算法 61
5-4 區域搜尋 65
5-5 適應函數 68
5-6 自適應搜尋框 68
第六章實驗結果與討論 71
6-1 人臉偵測實驗 73
6-2 人臉姿態辨識實驗 77
6-3 人臉追蹤實驗 82
第七章結論與建議 89
7-1 結論 89
7-2 建議 90
參考文獻 91
附錄 96

參考文獻

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指導教授

鍾鴻源(Hung-yuan Chung)

審核日期

2015-8-19

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