About

The eLog library was initially developed as a research prototype and later published for lifelogging researchers in 2010 to help them easily analyze heterogenous data and complex visualization. It has been kept growing with the progress of mobile computing environments and recently its UI part is released with GPL v3 license for wider usage. The eLog UI library is optimized for mobile environment and can get easily integrated with existing Web services.

Who We Are

The original work was proposed by Pil Ho and later extended the work with collaboration with 28 researchers around the world who contributed their lifelogs, collaborated for lifelog analysis and share research results to build up an open lifelogging platform for the public. Pil Ho has been keeping the development updating the library following up the progress in mobile computing.

Updates

  • Nov. 2014: Change the web page skin using bootstrap.
  • Nov. 2014: Published elog UI library as GPL v3.
  • Oct. 2014: Version up eLog library and documentation.

 

Implementing Event summarization on LifeLog Data

Project Member: Sajan Raj OJha

Problem Description
The influence of digital devices in human life cannot be ignored. Because of the easy availability of the digital devices the amount of digital data a human generates has grown enormously. The rich and vast amount of data that can be captured by these ubiquitous devices ranges from communication, location, proximity, motion, and video, to name a few. Recently, researchers are realizing the rich information that can be captured by these ubiquitous devices, which has potential impact on a vast range of domains including epidemiology, psychology and sociology, urban planning, security and intelligence, and health monitoring. The potential for use of this information is huge and mostly unexplored[1] . There is big research in the field of managing Personal Information. Personal Information Management (PIM) is an activity in which an individual stores his/her personal information items in order to retrieve and use them later. Such information items include files, emails, Web favorites, contacts, and notes . User has to personally search and summarize all the events himself, which is very daunting and cumbersome task. Managing them according to their nature for example grouping all the related images according to an event such as a Birthday Party. Mainly our focus is on the summarization and display of the event that has occurred in a person’s life.

Proposed Solution
We will try to build a system that is capable to summarize the images taken in near similar location along with GPS data. Image grouping will be done using different clustering techniques. Image clustering is a process of grouping images based on their similarity. The image clustering usually uses the color component, texture, edge, shape, or mixture of two components, etc[3].
The clustered image will help in exact event summarization in the particular location.

References
1. K. Farrahi and D. Gatica-Perez Discovering Routines from Large-Scale Human Locations using Probabilistic Topic Models ACM Transactions on Intelligent Systems and Technology, Special Issue on Activity Recognition, Vol. 2. No. 1, 2011.
2. Ofer Bergman, Ruth Beyth-Marom, Rafi Nachmias, Noa Gradovitch, and Steve Whittaker. 2008. Improved search engines and navigation preference in personal information management. ACM Trans. Inf. Syst. 26, 4, Article 20 (October 2008), 24 pages.
5. Journey on Image Clustering Based on Color Composition, Achmad Nizar Hidayanto, Elisabeth Martha Koeanan.

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