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The Analysis of Frequency Domain Characteristics of Emotional Images in Eye-tracking Experiment

机译:眼动实验中情感图像的频域特征分析

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Although recently eye-tracking method has been introduced into behavioral experiments based on dot-probe paradigm, some characteristics in eye-tracking data do not draw as much attention as traditional characteristics like reaction time. It is also necessary to associate eye-tracking data to characteristics of images shown in experiments. In this research, new variables, such as fixation length, times of fixation and times of eye movement, in eye-tracking data were extracted from a behavioral experiment based on dot probe paradigm. They were analyzed and compared to traditional reaction time. After the analysis of positive and negative scenery images, parameters such as hue frequency spectrum PAR (Peak to Average Ratio) were extracted and showed difference between negative and positive images. These parameters of emotional images could discriminate scenery images according to their emotions in an SVM classifier well. Besides, it was found that images' hue frequency spectrum PAR is obviously relevant to eye-tracking statistics. When the dot was on the negative side, negative images' hue frequency spectrum PAR and horizontal eye-jumps confirmed to hyperbolic distribution, while that of positive images was linear with horizontal eye-jumps. The result could help to explain the mechanism of human's attention and boost the study in computer vision.
机译:尽管最近将眼动追踪方法引入基于点探针范式的行为实验中,但眼动追踪数据中的某些特征并未像传统的反应时间那样吸引人们的注意。还需要将眼动数据与实验中显示的图像特征相关联。在这项研究中,从基于点探针范式的行为实验中提取了眼动数据中的新变量,如注视长度,注视时间和眼动时间。他们进行了分析,并与传统的反应时间进行了比较。在分析了正负风景图像之后,提取了诸如色调频谱PAR(峰均比)之类的参数,并显示了负正图像之间的差异。情感图像的这些参数可以在SVM分类器中根据它们的情感来区分风景图像。此外,还发现图像的色调频谱PAR显然与眼动统计有关。当点在负侧时,负像的色调频谱PAR和水平眼跳确认为双曲线分布,而正像的色相频谱与水平眼跳呈线性关系。该结果可帮助解释人们注意力的机制,并促进计算机视觉的研究。

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