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基于Shuffle-ZoeDepth單目深度估計(jì)的苗期
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Measurement Method of Seedling Stage Maize Height Based on Shuffle-ZoeDepth Monocular Depth Estimation
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    摘要:

    株高是鑒別玉米種質(zhì)性狀及作物活力的重要表型指標(biāo),苗期玉米遺傳特性表現(xiàn)明顯,,準(zhǔn)確測(cè)量苗期玉米植株高度對(duì)玉米遺傳特性鑒別與田間管理具有重要意義,。針對(duì)傳統(tǒng)植株高度獲取方法依賴人工測(cè)量,費(fèi)時(shí)費(fèi)力且存在主觀誤差的問題,,提出了一種融合混合注意力信息的改進(jìn)ZoeDepth單目深度估計(jì)模型,。改進(jìn)后的模型將Shuffle Attention模塊加入Decoder模塊的4個(gè)階段,使Decoder模塊在對(duì)低分辨率特征圖信息提取過程中能更關(guān)注特征圖中的有效信息,提升了模型關(guān)鍵信息的提取能力,,可生成更精確的深度圖,。為驗(yàn)證本研究方法的有效性,在NYU-V2深度數(shù)據(jù)集上進(jìn)行了驗(yàn)證,。結(jié)果表明,,改進(jìn)的Shuffle-ZoeDepth模型在NYU-V2深度數(shù)據(jù)集上絕對(duì)相對(duì)差、均方根誤差,、對(duì)數(shù)均方根誤差為0.083、0.301mm,、0.036,,不同閾值下準(zhǔn)確率分別為93.9%、99.1%,、99.8%,,均優(yōu)于ZoeDepth模型。同時(shí),,利用Shuffle-ZoeDepth單目深度估計(jì)模型結(jié)合玉米植株高度測(cè)量模型實(shí)現(xiàn)了苗期玉米植株高度的測(cè)量,,采集不同距離下苗期玉米圖像進(jìn)行植株高度測(cè)量試驗(yàn)。當(dāng)玉米高度在15~25cm,、25~35cm,、35~45cm3個(gè)區(qū)間時(shí),平均測(cè)量絕對(duì)誤差分別為1.41,、2.21,、2.08cm,平均測(cè)量百分比誤差分別為8.41%,、7.54%,、4.98%。試驗(yàn)結(jié)果表明該方法可僅使用單個(gè)RGB相機(jī)完成復(fù)雜室外環(huán)境下苗期玉米植株高度的精確測(cè)量,。

    Abstract:

    Plant height is an important phenotypic indicator for identifying maize germplasm traits and crop vigor, and maize genetic characteristics are obvious at the seedling stage, so accurate measurement of plant height at the seedling stage is of great significance for maize genetic characteristics identification and field management. Aiming at the problem that traditional plant height acquisition methods rely on manual measurement, which is time-consuming and subjective error, an improved ZoeDepth monocular depth estimation model incorporating mixed attention information was proposed. The improved model added the Shuffle Attention module to the various stages in the Decoder module, so that the Decoder module was more able to pay attention to the effective information in all the feature maps in the process of extracting information from the low-resolution feature maps, which enhanced the model’s ability of key information extraction, and could generate more accurate depth maps. In order to verify the effectiveness of the method, the validation was carried out on the NYU-V2 depth dataset, and the results showed that the ARE, RMSE, LG were 0.083, 0.301mm and 0.036, and the accuracy δ under different thresholds of the improved Shuffle-ZoeDepth model were 93.9%, 99.1% and 99.8%, respectively, all of which were better than those of the improved Shuffle-ZoeDepth model on NYU-V2 depth dataset.In addition, the Shuffle-ZoeDepth monocular depth estimation model combined with the maize plant height measurement model was used to complete the measurement of seedling maize plant height, and maize height measurement experiments were carried out by collecting images of seedling maize at different distances, and when the maize height was in the three height intervals of 15~25cm, 25~35cm, and 35~45cm, the AE were respectively 1.41cm, 2.21cm, and 2.08cm, and the PE were 8.41%, 7.54%, and 4.98%, respectively. The experimental results showed that this method can accomplish the accurate measurement of maize plant height at the seedling stage in complex environments using only a single RGB camera with a complex outdoor environment.

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趙永杰,蒲六如,宋磊,劉佳輝,宋懷波.基于Shuffle-ZoeDepth單目深度估計(jì)的苗期[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2024,55(5):235-243,253. ZHAO Yongjie, PU Liuru, SONG Lei, LIU Jiahui, SONG Huaibo. Measurement Method of Seedling Stage Maize Height Based on Shuffle-ZoeDepth Monocular Depth Estimation[J]. Transactions of the Chinese Society for Agricultural Machinery,2024,55(5):235-243,253.

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  • 收稿日期:2023-09-29
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  • 在線發(fā)布日期: 2023-12-06
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