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Smart Lifelog Retrieval System with Habit-based Concepts and Moment Visualization
| Content Provider | Semantic Scholar |
|---|---|
| Author | Suzuki, Tokinori Ikeda, Daisuke |
| Copyright Year | 2019 |
| Abstract | Our QUIK team participated in the Lifelog Semantic Access Subtask (LSAT) of the NTCIR-14 Lifelog-3 task. The task is that, given a topic of users’ daily activity or events (e.g. Find the moment when a user was taking a train from the city to home) as a query, a system retrieves the relevant images of the moments from users’ images of recording their daily lives. For LSAT task, we present an approach to retrieve users’ lifelog images by computing the similarity between users’ lifelog images and images obtained from the web by querying the LSAT topics into a web search engine. For computing the similarity between the lifelog images and images from the web, we employ a classifier trained on the images collected from the web with a convolutional neural network model. This paper describes our approach to solving LSAT task and reports the official results that we got. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings14/pdf/ntcir/03-NTCIR14-LIFELOG-SuzukiT-slides.pdf |
| Alternate Webpage(s) | http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings14/pdf/ntcir/03-NTCIR14-LIFELOG-SuzukiT.pdf |
| Alternate Webpage(s) | http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings14/pdf/ntcir/03-NTCIR14-LIFELOG-SuzukiT-poster.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
