本文選題：社交關系 + 關系檢索�。� 參考：《北京郵電大學》2013年碩士論文

【摘要】：人類的社交關系是社會活動的基本形式之一,互聯(lián)網(wǎng)技術的發(fā)展拉近了人與人之間距離,不管是線下還是線上,社交關系逐步成為人們維系感情聯(lián)系社會的一種方式。社交搜索作為下一代搜索引擎發(fā)展方向將有利于人們快速的獲取各種形式的社交關系。傳統(tǒng)的基于關鍵字的搜索由于其固有的重名低效等缺點將不適用于社交關系搜索系統(tǒng),本課題創(chuàng)新性地將基于內容的檢索技術運用到社交關系檢索系統(tǒng),使用正面人臉圖像代替人名關鍵詞進行檢索,是人臉識別領域的一個新型應用實踐,為用戶提供了一種智能化社交關系檢索體驗。 本課題主要研究并實現(xiàn)了基于人臉檢測與識別的社交關系檢索系統(tǒng)。該系統(tǒng)可以檢測用戶導入的圖像中的人臉和人物合照中的隱含的社交關系,并存儲這種關系,最后可以顯示待檢索的人臉的社交關系圖。本課題最終實現(xiàn)的系統(tǒng)是運行在Android平臺的智能手機上的,用戶通過手機的拍照功能可以很方便的獲取人物照片導入本系統(tǒng),從而進行相應的識別與檢索操作。 本論文首先介紹了人臉檢測與識別的經(jīng)典算法,詳細闡述了基于Adaboost的人臉檢測和PCA的人臉識別算法,并通過實驗證實了將其運用于智能終端平臺上的效率和正確率的可行性。針對關系拓撲圖中兩個結點上人物之間的關系親密度值,本文除了考慮每兩個人物的合照數(shù)作為權值,還借鑒了詞的激活度公式,加入單個人物存在的圖像個數(shù)作為一個參數(shù)。接下來論文通過需求分析和設計,實現(xiàn)了一個Android智能系統(tǒng)上的社交關系檢索系統(tǒng)。該系統(tǒng)不僅具有人臉檢測與識別、人臉庫和關系庫創(chuàng)建與更新和社交關系檢索等模塊,針對關系檢索的關系網(wǎng)狀圖還具有親密度檢索、關系查看和關系圖分享的功能。 最終系統(tǒng)測試結果表明,針對日常生活中人物照片,系統(tǒng)的人臉識別結果包括由相似度排序的n張人臉,識別的正確率隨n的增大而提升,當n=1時,識別的正確率較低,為47%左右,而當n=6時,識別的正確率可達97%左右。因此本系統(tǒng)在識別過程中都提供了6個結果,讓用戶通過手動選擇的輔助手段,進一步提高了識別準確率。另一方面,綜合考慮了詞激活度理論的關系親密度值比只考慮兩兩人物之間的合照數(shù)更符合統(tǒng)計規(guī)律。
[Abstract]:The social relationship of human beings is one of the basic forms of social activities. The development of Internet technology has brought people closer to each other. Whether offline or online, social relations have gradually become a way for people to maintain emotional ties with society. As a next-generation search engine, social search will help people to quickly obtain various forms of social relations. The traditional keyword-based search will not be suitable for the social relationship search system because of its inherent shortcomings such as low efficiency of the duplicate name. This paper innovatively applies the content-based retrieval technology to the social relationship search system. It is a new application practice in the field of face recognition to use frontal face image instead of human name keyword for retrieval. It provides a kind of intelligent social relationship retrieval experience for users. This paper mainly studies and implements a social relationship retrieval system based on face detection and recognition. The system can detect the implied social relationship between the face and the person in the image imported by the user and store the relationship. Finally, the social relationship graph of the face to be retrieved can be displayed. The final implementation of the system is run on the Android platform of the smart phone, the user can easily get the photo of the person into the system through the camera function, so as to carry out the corresponding identification and retrieval operations. In this paper, the classical face detection and recognition algorithms are introduced, and the face detection and recognition algorithms based on Adaboost are described in detail, and the feasibility of applying them to the intelligent terminal platform is proved by experiments. Aiming at the relationship affinity value between two persons on two nodes in the relation topology graph, this paper not only considers the number of each two characters as the weight value, but also draws on the formula of the activation degree of words, and adds the number of images existing in a single character as a parameter. Then, through requirement analysis and design, a social relationship retrieval system based on Android intelligent system is implemented. The system not only has the modules of face detection and recognition, human face database and relationship database creation and update, and social relationship retrieval, but also has the functions of close density retrieval, relationship view and relationship graph sharing. Finally, the system test results show that the face recognition results of the system include n faces sorted by similarity degree, and the recognition accuracy increases with the increase of n, and when n = 1, the recognition accuracy is lower. When n = 6, the correct rate of recognition is about 97%. Therefore, the system provides six results in the process of recognition, which allows users to further improve the recognition accuracy through the manual selection of auxiliary means. On the other hand, the relational affinity value of word activation theory is more consistent with the statistical law than only considering the number of pictures between two characters.
【學位授予單位】：北京郵電大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：TP391.41

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