基于結(jié)構(gòu)化建模方法的計算機(jī)視覺遮擋姿態(tài)估計研究

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摘要：本研究聚焦于計算機(jī)視覺領(lǐng)域的遮擋姿態(tài)估計問題，采用結(jié)構(gòu)化建模方法，深入分析遮擋條件下的姿態(tài)特征。通過構(gòu)建遮擋魯棒性模型，優(yōu)化姿態(tài)估計算法，有效提升了在復(fù)雜遮擋環(huán)境下的姿態(tài)估計精度與魯棒性，為計算機(jī)視覺技術(shù)的發(fā)展與應(yīng)用提供了有力支持。

關(guān)鍵詞：結(jié)構(gòu)化建模；計算機(jī)視覺；姿態(tài)估計；數(shù)據(jù)增強(qiáng)；圖像裁剪

doi：10.3969/J.ISSN.1672-7274.2025.01.019

中圖分類號：TP 391                 文獻(xiàn)標(biāo)志碼：A            文章編碼：1672-7274（2025）01-00-03

Research on Occluded Pose Estimation in Computer Vision Based on

Structured Modeling Approach

LIN Ziyao

（North China University of Technology， Beijing 100144， China）

Abstract： This study focuses on the problem of pose estimation with occlusion in the field of computer vision. By adopting a structured modeling approach， it deeply analyzes pose features under occlusion conditions. Through the construction of an occlusion-robust model and the optimization of pose estimation algorithms， the accuracy and robustness of pose estimation in complex occlusion environments are effectively improved， providing strong support for the development and application of computer vision technologies.

Keywords： structured modeling; computer vision; pose estimation; data augmentation; image cropping.

0   引言

本文致力于深入挖掘基于結(jié)構(gòu)化建模方法的遮擋姿態(tài)估計技術(shù)，通過創(chuàng)新模型架構(gòu)、優(yōu)化求解策略及遮擋感知機(jī)制，旨在全面提升姿態(tài)估計的準(zhǔn)確性與魯棒性，推動相關(guān)領(lǐng)域技術(shù)邁向新的高度。（剩余4256字）