{"title":"基于时域语义的远红外行人序列分割","authors":"Shaowu Peng, Zhenju Wang, Qiong Liu, Junying Chen","doi":"10.1117/12.2539449","DOIUrl":null,"url":null,"abstract":"This paper proposes the generation of a pedestrian ROI region, which is mainly aimed at pedestrian segmentation in far-infrared (FIR) images of in-vehicle systems. Since the FIR image is a grayscale image, the pixel value of the pedestrian is usually higher than the background, so the previous segmentation method is mainly threshold segmentation. However, this method will cause problems due to the uneven brightness of pedestrians caused by pedestrian wear, etc. We propose a new method for generating pedestrian ROI regions, which is based on the combination of image region merging and pixel-intensity vertical projection, and adopts the time domain semantic model to constrain the parameter space. Experiments show that our method has achieved good results in urban scenes.","PeriodicalId":384253,"journal":{"name":"International Symposium on Multispectral Image Processing and Pattern Recognition","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Far-infrared pedestrian sequence segmentation based on time domain semantics\",\"authors\":\"Shaowu Peng, Zhenju Wang, Qiong Liu, Junying Chen\",\"doi\":\"10.1117/12.2539449\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes the generation of a pedestrian ROI region, which is mainly aimed at pedestrian segmentation in far-infrared (FIR) images of in-vehicle systems. Since the FIR image is a grayscale image, the pixel value of the pedestrian is usually higher than the background, so the previous segmentation method is mainly threshold segmentation. However, this method will cause problems due to the uneven brightness of pedestrians caused by pedestrian wear, etc. We propose a new method for generating pedestrian ROI regions, which is based on the combination of image region merging and pixel-intensity vertical projection, and adopts the time domain semantic model to constrain the parameter space. Experiments show that our method has achieved good results in urban scenes.\",\"PeriodicalId\":384253,\"journal\":{\"name\":\"International Symposium on Multispectral Image Processing and Pattern Recognition\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-02-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Symposium on Multispectral Image Processing and Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2539449\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Symposium on Multispectral Image Processing and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2539449","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Far-infrared pedestrian sequence segmentation based on time domain semantics
This paper proposes the generation of a pedestrian ROI region, which is mainly aimed at pedestrian segmentation in far-infrared (FIR) images of in-vehicle systems. Since the FIR image is a grayscale image, the pixel value of the pedestrian is usually higher than the background, so the previous segmentation method is mainly threshold segmentation. However, this method will cause problems due to the uneven brightness of pedestrians caused by pedestrian wear, etc. We propose a new method for generating pedestrian ROI regions, which is based on the combination of image region merging and pixel-intensity vertical projection, and adopts the time domain semantic model to constrain the parameter space. Experiments show that our method has achieved good results in urban scenes.