本文選題：行人再識別 + 分塊匹配��； 參考：《計算機應(yīng)用研究》2017年04期

【摘要】：針對行人再識別精度低的難題進行研究,提出了一種新的基于分塊匹配的行人再識別方法。首先,引入帶人體結(jié)構(gòu)信息的人體DPM對行人外觀進行分割,得到的帶語義信息的身體部件作為匹配識別的基本單元;其次,基于深度神經(jīng)網(wǎng)絡(luò)模型提取各部件的深度特征作為匹配依據(jù);再次,基于余弦距離判斷各身體部件與目標(biāo)行人對應(yīng)部件的相似性;最后,融合所有身體部件的識別結(jié)果得到最終的再識別結(jié)果。實驗結(jié)果表明,跟已有方法相比,該方法具有更好的魯棒性,在識別精度上有較明顯的優(yōu)勢。
[Abstract]:A new method of pedestrian rerecognition based on block matching is proposed to solve the problem of low accuracy of pedestrian rerecognition. Firstly, the human body DPM with human structure information is introduced to segment the appearance of pedestrians, and the body parts with semantic information are used as the basic unit of matching recognition. Based on the depth neural network model to extract the depth features of each component as the matching basis; thirdly, based on the cosine distance to judge the similarity between the body parts and the target pedestrian corresponding parts; finally, Fusion of all body parts of the recognition results to obtain the final recognition results. The experimental results show that the proposed method is more robust than the existing methods and has obvious advantages in recognition accuracy.
【作者單位】： 國家數(shù)字交換系統(tǒng)工程技術(shù)研究中心;
【基金】：國家自然科學(xué)基金資助項目(61521003,61379151) 國家科技支撐計劃資助項目(2014BAH30B01) 河南省杰出青年基金資助項目(144100510001)
【分類號】：TP391.41;TP183
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本文編號：1823915