利用注视数据对漫画进行分割和影响

Proceedings of the ACM Symposium on Applied Perception Pub Date : 2016-07-22 DOI:10.1145/2931002.2947703

Ishwarya Thirunarayanan, S. Koppal, J. Shea, Eakta Jain

{"title":"利用注视数据对漫画进行分割和影响","authors":"Ishwarya Thirunarayanan, S. Koppal, J. Shea, Eakta Jain","doi":"10.1145/2931002.2947703","DOIUrl":null,"url":null,"abstract":"In this work, we present a semi-automatic method based on gaze data to identify the objects in comic images on which digital effects will look best. Our key contribution is a robust technique to cluster the noisy gaze data without having to specify the number of clusters as input. We also present an approach to segment the identified object of interest.","PeriodicalId":102213,"journal":{"name":"Proceedings of the ACM Symposium on Applied Perception","volume":"123 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Leveraging gaze data for segmentation and effects on comics\",\"authors\":\"Ishwarya Thirunarayanan, S. Koppal, J. Shea, Eakta Jain\",\"doi\":\"10.1145/2931002.2947703\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work, we present a semi-automatic method based on gaze data to identify the objects in comic images on which digital effects will look best. Our key contribution is a robust technique to cluster the noisy gaze data without having to specify the number of clusters as input. We also present an approach to segment the identified object of interest.\",\"PeriodicalId\":102213,\"journal\":{\"name\":\"Proceedings of the ACM Symposium on Applied Perception\",\"volume\":\"123 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-07-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the ACM Symposium on Applied Perception\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2931002.2947703\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ACM Symposium on Applied Perception","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2931002.2947703","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

在这项工作中，我们提出了一种基于注视数据的半自动方法来识别漫画图像中数字效果最好的物体。我们的关键贡献是一种鲁棒的技术，可以在不指定群集数量作为输入的情况下对噪声凝视数据进行聚类。我们还提出了一种分割感兴趣的识别对象的方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Leveraging gaze data for segmentation and effects on comics

In this work, we present a semi-automatic method based on gaze data to identify the objects in comic images on which digital effects will look best. Our key contribution is a robust technique to cluster the noisy gaze data without having to specify the number of clusters as input. We also present an approach to segment the identified object of interest.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Proceedings of the ACM Symposium on Applied Perception

自引率

0.00%

发文量