本文選題：壓縮感知 + 目標檢測��； 參考：《北京郵電大學》2016年碩士論文

【摘要】：多目標實時跟蹤是計算機視覺領域的研究熱點之一,在智能交通、智能監(jiān)控等多個領域有著廣泛的應用,然而設計一個魯棒性高的多目標實時跟蹤系統(tǒng),無論是對科學研究還是工程實踐都極具挑戰(zhàn)性。壓縮感知算法通過對信號采樣壓縮,能夠大大降低信號的復雜度。將壓縮感知理論與多目標實時跟蹤相結合能夠提升系統(tǒng)跟蹤的穩(wěn)定性和實時性。本文基于壓縮感知理論,設計了一套魯棒性高的多目標實時跟蹤系統(tǒng)。主要研究內容如下:(1)研究并實現(xiàn)了基于Haar特征的AdaBoost目標檢測器。提取視頻圖像的Haar特征,并基于大量多角度人頭正負樣本圖像訓練AdaBoost級聯(lián)分類器,實現(xiàn)多目標檢測。(2)設計并改進了基于壓縮感知的樸素貝葉斯目標跟蹤器。基于壓縮感知理論,對目標特征采樣獲得壓縮感知特征,并構建分特.征權重的樸素貝葉斯在線學習分類器,實現(xiàn)多目標實時跟蹤。(3)開發(fā)了一套多目標實時跟蹤系統(tǒng),在多種實驗場景下與MHT算和CT算法進行檢測跟蹤實驗比較,證明本系統(tǒng)在實時性、準確性和穩(wěn)定性上都有較好的表現(xiàn)。本文將壓縮感知算法應用到目標跟蹤系統(tǒng)中,實現(xiàn)了目標跟蹤系統(tǒng)穩(wěn)定性和實時性的兼?zhèn)涞亩嗄繕藢崟r跟蹤系統(tǒng),具有很高的工程研究價值和社會應用價值。
[Abstract]:Multi-target real-time tracking is one of the hotspots in the field of computer vision. It has been widely used in many fields, such as intelligent transportation, intelligent monitoring and so on. However, a robust multi-target real-time tracking system is designed. Both scientific research and engineering practice are extremely challenging. The compression sensing algorithm can greatly reduce the complexity of the signal by sampling and compressing the signal. Combining compression sensing theory with multi-target real-time tracking can improve the stability and real-time of system tracking. Based on the theory of compressed sensing, a robust multi-target real-time tracking system is designed in this paper. The main contents are as follows: (1) AdaBoost target detector based on Haar feature is studied and implemented. The Haar feature of video image is extracted and the AdaBoost cascade classifier is trained based on a large number of multi-angle head positive and negative samples. (2) A naive Bayesian target tracker based on compressed sensing is designed and improved. Based on the theory of compressed perception, the compressed perceptual features are obtained by sampling the target features, and the sub-features are constructed. Naive Bayesian online learning classifier with eigenweight is used to realize multi-target real-time tracking. (3) A multi-target real-time tracking system is developed and compared with MHT algorithm and CT algorithm in various experimental scenarios. It is proved that the system has good performance in real time, accuracy and stability. In this paper, the compressed sensing algorithm is applied to the target tracking system, and the multi-target real-time tracking system is realized, which is both stable and real-time. It has high engineering research value and social application value.
【學位授予單位】：北京郵電大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：TP391.41

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本文編號：2103017