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  本文關鍵詞： 壓縮感知 置信圖 超像素 目標跟蹤　出處：《天津大學》2016年碩士論文　論文類型：學位論文

【摘要】：復雜場景下的目標跟蹤是計算機視覺領域最熱點的課題之一。經(jīng)過幾十年的研究,目標跟蹤技術有了長足的發(fā)展,并在視頻監(jiān)控、智能交通、人機交互等民用和軍事領域上都有廣泛的應用。但在實際應用中,目標跟蹤依然是很有挑戰(zhàn)的問題,例如光照變化、目標外觀變化,目標被遮擋和復雜背景干擾等眾多因素。這些因素對目標跟蹤算法的魯棒性和實時性提出很高的要求。當前,基于壓縮感知理論的跟蹤算法通過應用隨機測量矩陣去壓縮圖像信號來提取低維特征,極大地提高跟蹤算法的實時性且越來越引起人們注意。然而當前景目標和背景在形狀或者紋理相似時,跟蹤結果可能并不準確。針對此,本文提出基于超像素的壓縮感知跟蹤(Superpixel-based compressive tracking,SCT)算法,該算法根據(jù)新來的幀和目標在超像素之間的相似性來構建置信圖。超像素塊能把像素聚合成有意義原子區(qū)域,SCT算法吸收其優(yōu)點。置信圖提供很強的證據(jù)用來度量目標出現(xiàn)的可能性,這能夠捕捉到在超像素級別目標和背景局部外觀顏色的不同,同時改進實時壓縮感知跟蹤(Fast compressive tracking,FCT)算法的粗粒度到細粒度搜索策略。綜上,本文提出基于超像素的壓縮感知跟蹤算法,該算法不僅考慮到目標和背景在形狀或者紋理的不同,而且充分利用超像素級別判別性強的顏色描述子構建的置信圖提供指導。在具挑戰(zhàn)性視頻序列上的實驗結果表明就準確性和魯棒性而言提出的算法優(yōu)于最新水平的算法。
[Abstract]:Target tracking in complex scenes is one of the hottest topics in the field of computer vision. After decades of research, target tracking technology has made great progress, and in video surveillance, intelligent transportation, It is widely used in civil and military fields, such as human-computer interaction. But in practical application, target tracking is still a challenging problem, such as illumination change, target appearance change, There are many factors, such as target occlusion and complex background interference. These factors require high robustness and real-time performance of target tracking algorithm. The tracking algorithm based on compressed sensing theory extracts low-dimensional features by using random measurement matrix to compress image signals. It greatly improves the real-time performance of the tracking algorithm and attracts more and more attention. However, when the foreground target and background are similar in shape or texture, the tracking results may not be accurate. In this paper, a super-pixel based compressive tracking algorithm is proposed. According to the similarity between the new frame and the target, the algorithm constructs the confidence chart. The superpixel block can aggregate the pixels into a meaningful atomic region and the SCT algorithm absorbs its advantages. The confidence chart provides a strong evidence for measurement. The possibility of a target, This can capture the difference in local appearance colors between targets and backgrounds at the super-pixel level, while improving the coarse-grained to fine-grained search strategy of the Fast compressive tracking algorithm for real-time compression awareness tracking. In this paper, a compression sensing tracking algorithm based on hyperpixel is proposed. This algorithm not only takes into account the difference of object and background in shape or texture. The experimental results on challenging video sequences show that the proposed algorithm is superior to the latest algorithm in terms of accuracy and robustness.
【學位授予單位】：天津大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：TP391.41

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1 周健;基于超像素的壓縮感知跟蹤[D];天津大學;2016年

2 王君;近周期結構性遮擋物檢測與去除[D];天津大學;2016年

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本文編號：1548173