基于OpenCV的中遠距離人臉檢測

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基于OpenCV的中遠距離人臉檢測(論文15000字)
摘  要
人臉檢測技術,是指利用計算機采用一定的算法或者策略,在動態或者復雜的場景、背景中檢測出人的臉部的存在,并確定人臉的位置、大小以的技術。作為人臉識別、表情識別、人臉跟蹤等技術的基礎和前提技術,人臉檢測技術在智能控制、模式識別等其他領域也引起了廣發的重視。
本論文主要介紹的是基于OpenCV的人臉檢測應用程序的開發,簡單介紹了國內外人臉識別技術研究及應用的發展現狀及其重難點分析。
在第二章重點分析了AdaBoost算法中集成機器學習的一個重要機制:多個弱分類器集成的方法,機器學習中的弱學習到強學習,集成的關鍵是投票,最簡單的方法是“絕對多數”的方法,詳細分析了AdaBoost算法檢測速度快、可以檢測任意尺度的圖像的特點。
本人開發的人臉檢測和識別軟件是基于OpenCV的Haar級聯分類器進行人臉識別,通過對OpenCV開源代碼的研究學習,掌握了OpenCV提供的重要的圖像分析和處理函數以及基礎的數據類型、幫助的數據類型,并Visual C++集成開發環境做平臺下搭建了基于OpenCV的人臉檢測系統。通過對實例空間內大量圖像內對目標區域即人臉的識別,證明了利用Harr級聯分類器來進行人臉檢測和識別的方法是一種速度快、精度高的方法。

關鍵字:人臉檢測;AdaBoost;分類器;OpenCV
 
ABSTRACT
Human face detection means that for a given image or video,to determine whether it contains face regions,if so,determines the number, the exact location and the size of all the faces.Human face detection is not only a necessary precondition of face recognition,expression recognition technology, face tracking,but also,it plays ail important role in applications like in the intelligent human-computer interaction,video conferencing,intelligent surveillance,video retrieval and so on.Therefore,face detection technology attracted widespread attention in pattern recognition,computer vision,human-computer interaction and other fields.
This paper mainly introduces the number of face detection application program which is based on the OpenCV. This paper describes the national and international recognition technology applications research and development and analysis the difficult situation.
In chapter 2 on the analysis of the AdaBoost algorithms integration of machinery to study of an important mechanism : more integrated approach in the classification of the study of study at the learning and integration is the key to the vote, the simplest method is the absolute majority . Also, detailed analysis AdaBoost algorithm test speed, you can detect any scale the image quality.
I developed the application program by using the Haar cascade classifier of the OpenCV for face recognition. The so-called Haar cascade classifier is a greater level of classifier which is associated with several simple boost classifiers, the detected targets pass through each classifier, the one who passed through all he classifiers can be judged as the face region. By the experiment of sample photos recognition, it proved that the Harr cascade classifier face-detection method is a kind of high speed and precision method.
This paper’s research is based on the OpenCV source code,in which some basic data type and helping data type were created,and because of the opermess of the code,we build a human face detection system in the Visual C++ environment.

Key words: face detection ; AdaBoost ; classifier ; OpenCV
 
目  錄
1. 概述    1
1.1 引言    1
1.2概念介紹    2
1.3 研究現狀    3
1.4 應用領域    4
1.4 評價標準    5
2. Adaboost人臉檢測算法    6
2.1 概述    6
2.1.1 Adaboost算法簡介    6
2.1.2 Adaboost人臉檢測算法    6
2.2弱學習與強學習    7
2.3 PAC基本模型    8
2.3.1 概述    8
2.3.2 基本概念    8
2.3.3 PAC模型的不足    9
2.4 Boosting算法    9
2.5 Adaboost算法性能分析    10
3. OpenCV訓練分類器    11
3.1 OpenCV平臺概述    11
3.1.1 OpenCV簡介    11
3.1.2 OpenCV函數    11
3.1.3 OpenCV特征    12
3.2 目標檢測法    12
3.3 樣本的創建    13
3.3.1創建負樣本(反例樣本)    14
3.3.2創建正樣本(正例樣本)    14
3.4訓練分類器    16
3.5 檢測目標    19
3.6創建Haar特征并載入樣本    19
3.6.1  載入正樣本    19
3.6.2  載入負樣本    20
3.6.3  計算Haar特征值并生成XML文件    21
4. 核心實驗設計    23
4.1程序流程圖    23
4.2關鍵代碼    23
4.3為何增加檢測視頻記錄    25
4.3各個分類器處理結果對比    25
5. 結 論    28
致謝    29
參考文獻    30
附錄:人臉檢測主程序    31

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