Towards reliable object representation via sparse directional patches and spatial center cues  

作　　者：Muwei Jian Hui Yu 

机构地区：[1]School of Computer Science and Technology,Shandong University of Finance and Economics,Jinan 250014,China [2]School of Creative Technologies,University of Portsmouth,Portsmouth 200021,UK

出　　处：《Fundamental Research》2025年第1期354-359,共6页自然科学基础研究(英文版)

基　　金：supported by National Natural Science Foundation of China(61976123,61601427);Taishan Young Scholars Program of Shandong Province;Key Development Program for Basic Research of Shandong Province(ZR2020ZD44);Royal Society-K.C.Wong International Fellowship(NIF\R1\180909).

摘　　要：In the process of image understanding,the human visual system(HVS)performs multiscale analysis on various objects.HVS primarily focuses on marginally conspicuous image patches located within or around distinct objects rather than scanning the image pixels point by point.Inspired by the HVS mechanism,in this paper,we aimed to describe and exploit multiscale decomposition-based patch detection models for automatic visual feature representation and object localization in images.Our investigation into mimicking and modeling the HVS to capture conspicuous sparse patches and their spatial distribution clues makes a profound contribution to the automatic comprehension and characterization of images by machines.This study demonstrates that the sparse patch-based visual representation with spatial center cues is intrinsically tolerant to object positioning and understanding beyond object variations in spatial position,multiresolution,and chrominance,which has significant implications for many vision-based automatic object grabbing and perception applications,such as robotics,human‒machine interaction,and unmanned aerial vehicles(UAVs).

关 键 词：Multiscale analysis Image patches Visual perception Shearlet transform Object representation 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]