The existing methods of landscape visual quality evaluation is mostly based on people's subjective feelings,and the objectivity and scientificity of evaluation results are insufficient.As an important means of exp...The existing methods of landscape visual quality evaluation is mostly based on people's subjective feelings,and the objectivity and scientificity of evaluation results are insufficient.As an important means of experimental psychology,eye movement technology can show great advantages and potential in landscape visual quality evaluation.On the basis of combing and summarizing the relevant literature,based on the explanation of the technical principle of eye movement analysis,the application field,research content,technical methods and other aspects of eye movement analysis were reviewed.The application prospect of eye movement technology in landscape visual quality evaluation was explored to provide theoretical reference for the in-depth evaluation and research of landscape visual quality evaluation theory.展开更多
The evaluation index of camouflage patterns is important in the field of military application.It is the goal that researchers have always pursued to make the computable evaluation indicators more in line with the huma...The evaluation index of camouflage patterns is important in the field of military application.It is the goal that researchers have always pursued to make the computable evaluation indicators more in line with the human visual mechanism.In order to make the evaluation method more computationally intelligent,a Multi-Feature Camouflage Fused Index(MF-CFI)is proposed based on the comparison of grayscale,color and texture features between the target and the background.In order to verify the effectiveness of the proposed index,eye movement experiments are conducted to compare the proposed index with existing indexes including Universal Image Quality Index(UIQI),Camouflage Similarity Index(CSI)and Structural Similarity(SSIM).Twenty-four different simulated targets are designed in a grassland background,28 observers participate in the experiment and record the eye movement data during the observation process.The results show that the highest Pearson correlation coefficient is observed between MF-CFI and the eye movement data,both in the designed digital camouflage patterns and largespot camouflage patterns.Since MF-CFI is more in line with the detection law of camouflage targets in human visual perception,the proposed index can be used for the comparison and parameter optimization of camouflage design algorithms.展开更多
基金Supported by the National Natural Science Foundation of China(32001366)General Project of China Postdoctoral Science Foundation(2022M710403).
文摘The existing methods of landscape visual quality evaluation is mostly based on people's subjective feelings,and the objectivity and scientificity of evaluation results are insufficient.As an important means of experimental psychology,eye movement technology can show great advantages and potential in landscape visual quality evaluation.On the basis of combing and summarizing the relevant literature,based on the explanation of the technical principle of eye movement analysis,the application field,research content,technical methods and other aspects of eye movement analysis were reviewed.The application prospect of eye movement technology in landscape visual quality evaluation was explored to provide theoretical reference for the in-depth evaluation and research of landscape visual quality evaluation theory.
基金Natural Science Foundation of Jiangsu Province&Key Laboratory Foundation,grant number is BK20180579&6142206180204 respectively.
文摘The evaluation index of camouflage patterns is important in the field of military application.It is the goal that researchers have always pursued to make the computable evaluation indicators more in line with the human visual mechanism.In order to make the evaluation method more computationally intelligent,a Multi-Feature Camouflage Fused Index(MF-CFI)is proposed based on the comparison of grayscale,color and texture features between the target and the background.In order to verify the effectiveness of the proposed index,eye movement experiments are conducted to compare the proposed index with existing indexes including Universal Image Quality Index(UIQI),Camouflage Similarity Index(CSI)and Structural Similarity(SSIM).Twenty-four different simulated targets are designed in a grassland background,28 observers participate in the experiment and record the eye movement data during the observation process.The results show that the highest Pearson correlation coefficient is observed between MF-CFI and the eye movement data,both in the designed digital camouflage patterns and largespot camouflage patterns.Since MF-CFI is more in line with the detection law of camouflage targets in human visual perception,the proposed index can be used for the comparison and parameter optimization of camouflage design algorithms.
