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Photo linker: a system for finding your old photos based on fragmentary memories

Published: 19 August 2015 Publication History

Abstract

With the rapid spread of image capture devices, the size of family album grows quickly up. It is difficult for family members to find out an expected photo just based on their fragmentary memory. In this paper, we attempt to develop a system named Photo Linker, to help people quickly get their expected photos by fully exploring the clues remembered by themselves. The key idea is to build the relationship among all photos by shared faces and scenes. The system includes three key components: (1) face detection and recognition; (2) scene classification; (3) association searching. In particular, an algorithm called "Association Correction" based on FP-Growth is discovered to improve the face recognition rate of family members. Moreover, a friendly interface is designed and implemented to facilitate the photo searching process. The experimental results show that the system can effectively and efficiently build the relationship among photos and make the photo finding process more convenient.

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Published In

cover image ACM Other conferences
ICIMCS '15: Proceedings of the 7th International Conference on Internet Multimedia Computing and Service
August 2015
397 pages
ISBN:9781450335287
DOI:10.1145/2808492
  • General Chairs:
  • Ramesh Jain,
  • Shuqiang Jiang,
  • Program Chairs:
  • John Smith,
  • Jitao Sang,
  • Guohui Li
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 August 2015

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Author Tags

  1. data mining
  2. face detection
  3. face recognition
  4. scene classification
  5. systems

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  • Research-article

Funding Sources

  • Program for Changjiang Scholars and Innovative Research Team in University
  • National Basic Research Program of China
  • Fundamental Research Funds for the Central Universities
  • Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering, China Three Gorges University, China
  • National Natural Science Foundation of China

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ICIMCS '15

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ICIMCS '15 Paper Acceptance Rate 20 of 128 submissions, 16%;
Overall Acceptance Rate 163 of 456 submissions, 36%

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