{"title":"用于移动线条检索的局部形状描述符","authors":"Y. Xuan, Ling-yu Duan, Tiejun Huang","doi":"10.1109/VCIP.2013.6706378","DOIUrl":null,"url":null,"abstract":"Coming with the rapid spread of Intelligent terminals with camera, mobile visual search techniques have undergone a revolution, where visual information can be easily browsed and retrieved upon simply capturing a query photo. However, most existing work targets at compact description of natural scene image statistics, while dealing with line drawing images retains an open problem. This paper presents a unified framework of line drawing problems in mobile visual search. We propose a compact description of line drawing image named Local Inner-Distance Shape Context (LISC) which is robust to the distortion and occlusion and enjoys scale and rotation invariance. Together with an innovative compression scheme using JBIG2 to reduce query delivery latency, our framework works well on both a self-built dataset and MPEG- 7 CE Shape-1 dataset. Promising results on both datasets show significant improvement over state-of-the-art algorithms.","PeriodicalId":407080,"journal":{"name":"2013 Visual Communications and Image Processing (VCIP)","volume":"1630 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A local shape descriptor for mobile linedrawing retrieval\",\"authors\":\"Y. Xuan, Ling-yu Duan, Tiejun Huang\",\"doi\":\"10.1109/VCIP.2013.6706378\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Coming with the rapid spread of Intelligent terminals with camera, mobile visual search techniques have undergone a revolution, where visual information can be easily browsed and retrieved upon simply capturing a query photo. However, most existing work targets at compact description of natural scene image statistics, while dealing with line drawing images retains an open problem. This paper presents a unified framework of line drawing problems in mobile visual search. We propose a compact description of line drawing image named Local Inner-Distance Shape Context (LISC) which is robust to the distortion and occlusion and enjoys scale and rotation invariance. Together with an innovative compression scheme using JBIG2 to reduce query delivery latency, our framework works well on both a self-built dataset and MPEG- 7 CE Shape-1 dataset. Promising results on both datasets show significant improvement over state-of-the-art algorithms.\",\"PeriodicalId\":407080,\"journal\":{\"name\":\"2013 Visual Communications and Image Processing (VCIP)\",\"volume\":\"1630 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 Visual Communications and Image Processing (VCIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VCIP.2013.6706378\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Visual Communications and Image Processing (VCIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VCIP.2013.6706378","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
随着带摄像头的智能终端的迅速普及,移动视觉搜索技术发生了一场革命,只需拍摄一张查询照片就可以轻松浏览和检索视觉信息。然而,大多数现有的工作都是针对自然场景图像统计的紧凑描述,而处理线条绘制图像仍然是一个开放的问题。本文提出了移动视觉搜索中线条绘制问题的统一框架。我们提出了一种紧凑的线条图像描述方法,称为局部内距离形状上下文(LISC),该方法对扭曲和遮挡具有鲁棒性,并且具有尺度和旋转不变性。结合使用JBIG2的创新压缩方案来减少查询交付延迟,我们的框架在自建数据集和MPEG- 7 CE Shape-1数据集上都能很好地工作。在这两个数据集上的令人鼓舞的结果表明,与最先进的算法相比,有了显著的改进。
A local shape descriptor for mobile linedrawing retrieval
Coming with the rapid spread of Intelligent terminals with camera, mobile visual search techniques have undergone a revolution, where visual information can be easily browsed and retrieved upon simply capturing a query photo. However, most existing work targets at compact description of natural scene image statistics, while dealing with line drawing images retains an open problem. This paper presents a unified framework of line drawing problems in mobile visual search. We propose a compact description of line drawing image named Local Inner-Distance Shape Context (LISC) which is robust to the distortion and occlusion and enjoys scale and rotation invariance. Together with an innovative compression scheme using JBIG2 to reduce query delivery latency, our framework works well on both a self-built dataset and MPEG- 7 CE Shape-1 dataset. Promising results on both datasets show significant improvement over state-of-the-art algorithms.