本文選題：Android平臺　切入點：智能監(jiān)控　出處：《江蘇科技大學》2017年碩士論文

【摘要】：隨著4G網絡的普及,智能手機已經是日常生活中不可缺少的一部分,同時安防監(jiān)控也是日常生活中值得關注的問題。為了改善傳統(tǒng)視頻監(jiān)控系統(tǒng)主動預警功能不強、避免在事后取證時觀看大量的無效靜止場景的視頻錄像,實現(xiàn)監(jiān)控時達到主動預警的目的,本文設計了一個基于移動終端的主動預警系統(tǒng)。本文根據實際監(jiān)控場景的多樣化,對運動目標檢測采用背景建模的方法,同時增加場景中人臉檢測。針對實際問題,研究了有關文獻,介紹了與智能監(jiān)控相關的方法和技術。本文研究了采用背景差分法、光流法、幀差法對運動目標進行檢測的方法和技術;研究了PCA算法、Fisher臉法、Adaboost算法和Haar級聯(lián)中的boosting算法等人臉識別算法。在視屏傳輸算法方面,主要研究了H.264的RTP封包算法以及其具體過程。為了在移動終端的實現(xiàn)主動預警,本文在Android平臺下,按照軟件工程的設計的規(guī)范,對移動終端中主動預警系統(tǒng)進行了需求分析、系統(tǒng)設計和實現(xiàn)。本項目實現(xiàn)的主動預警系統(tǒng)包括服務器端服務程序和移動終端的應用程序。服務器端實現(xiàn)了有場景變化時就錄制視頻并保存,在主動預警方面,提出分級預警策略,使得系統(tǒng)減少誤報,保障了系統(tǒng)的可用性,使得用戶在移動端接收到報警信息后,根據報警級別采取相應措施,及時地處理。在研究的過程中,還針視頻監(jiān)控傳輸視頻數(shù)據過程中數(shù)據量大的問題,對H.264算法進行了研究和改進,使得本項目研究的主動預警系統(tǒng)實時性得到了提高。另外,為了對視屏監(jiān)控中的入侵對象進行區(qū)分,本文對人臉識別算法行了研究,通過人臉識別來輔助判斷的入侵對象,提高主動預警準確率,減少誤報的概率。本課題通過對運動目標檢測、人臉檢測及視頻傳輸技術的研究,研發(fā)實現(xiàn)了一個基于移動終端的主動預警系統(tǒng)。
[Abstract]:With the popularity of 4G network, smart phone is an indispensable part of daily life, and security monitoring is also a problem worth paying attention to in daily life.In order to improve the traditional video surveillance system active warning function is not strong, avoid watching a large number of video videos of invalid static scene after evidence collection, and achieve the purpose of active early warning when monitoring.An active early warning system based on mobile terminal is designed in this paper.According to the diversity of the actual monitoring scene, the background modeling method is used to detect moving targets, and the face detection in the scene is added at the same time.In view of the practical problems, the related literature is studied, and the methods and techniques related to intelligent monitoring are introduced.In this paper, the background difference method, optical flow method and frame difference method are used to detect moving targets, and face recognition algorithms such as PCA algorithm and boosting algorithm in Haar cascade are studied.In video transmission algorithm, H.264 RTP packet algorithm and its specific process are studied.In order to realize active early warning in mobile terminal, according to the design standard of software engineering, the requirement analysis, system design and implementation of active early warning system in mobile terminal are carried out in this paper based on Android platform.This project realizes the active early warning system including server-side service program and mobile terminal application program.The server can record the video and save the video when the scene changes. In the aspect of active early warning, a hierarchical warning strategy is put forward, which can reduce the false positives, ensure the usability of the system, and make the user receive the alarm information in the mobile terminal.Take appropriate measures according to the alarm level and deal with them in time.In the process of research, the problem of large amount of data in video surveillance and transmission process is discussed. The H.264 algorithm is studied and improved, which improves the real-time performance of the active early warning system studied in this project.In addition, in order to distinguish the intrusion objects in video surveillance, this paper studies the face recognition algorithm, through face recognition to assist the judgment of the intrusion object, improve the accuracy of active early warning, reduce the probability of false positives.Based on the research of moving target detection, face detection and video transmission, an active early warning system based on mobile terminal is developed.
【學位授予單位】：江蘇科技大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP391.41;TP277

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