2019 Digital Image Computing: Techniques and Applications (DICTA)最新文献

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AB-PointNet for 3D Point Cloud Recognition AB-PointNet用于三维点云识别
2019 Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2019-04-08 DOI: 10.1109/DICTA47822.2019.8945926
J. Komori, K. Hotta
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引用次数: 3
Conference Chairs and Committees 会议主席和委员会
2019 Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2018-12-01 DOI: 10.1109/E-SCIENCE.2005.25
{"title":"Conference Chairs and Committees","authors":"","doi":"10.1109/E-SCIENCE.2005.25","DOIUrl":"https://doi.org/10.1109/E-SCIENCE.2005.25","url":null,"abstract":"","PeriodicalId":6696,"journal":{"name":"2019 Digital Image Computing: Techniques and Applications (DICTA)","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82438042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Visual Localization under Appearance Change: A Filtering Approach 外观变化下的视觉定位:一种滤波方法
2019 Digital Image Computing: Techniques and Applications (DICTA) Pub Date : 2018-11-20 DOI: 10.1109/DICTA47822.2019.8945810
Anh-Dzung Doan, Y. Latif, Tat-Jun Chin, Yu Liu, Shin-Fang Ch'ng, Thanh-Toan Do, I. Reid
{"title":"Visual Localization under Appearance Change: A Filtering Approach","authors":"Anh-Dzung Doan, Y. Latif, Tat-Jun Chin, Yu Liu, Shin-Fang Ch'ng, Thanh-Toan Do, I. Reid","doi":"10.1109/DICTA47822.2019.8945810","DOIUrl":"https://doi.org/10.1109/DICTA47822.2019.8945810","url":null,"abstract":"A major focus of current research on place recognition is visual localization for autonomous driving. In this scenario, as cameras will be operating continuously, it is realistic to expect videos as an input to visual localization algorithms, as opposed to the single-image querying approach used in other place recognition works. In this paper, we show that exploiting temporal continuity in the testing sequence significantly improves visual localization — qualitatively and quantitatively. Although intuitive, this idea has not been fully explored in recent works. Our main contribution is a novel Monte Carlo-based visual localization technique that can efficiently reason over the image sequence. Also, we propose an image retrieval pipeline which relies on local features and an encoding technique to represent an image as a single vector. The experimental results show that our proposed method achieves better results than state-of-the-art approaches for the task on visual localization under significant appearance change. Our synthetic dataset is made available at: http://tiny.cc/jd73bz","PeriodicalId":6696,"journal":{"name":"2019 Digital Image Computing: Techniques and Applications (DICTA)","volume":"91 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2018-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79524081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
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