eLifeLog.org Labs is a collection of on-going experiments by members. Feel free to create your own one to show off your ideas and get some feedbacks or help from experts in eLifeLog.
The E-log project is an acronym of our main lifelog research works composed of various sub laboratories (See the below) aiming to develop a system for life logging that may cover personal diary, healthcare, fitness, surveillance, security and/or enterprise management: e-Log Project
Lifelog data is diverse in all aspects. This category is a collection of lifelog data analysis using our own data, contributed data or public data. Labs include preliminary data analysis or technical development for lifelog mining: Lifelog Mining
|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. The clustered image will help in exact event summarization in the particular location.|
|We want to address the problem of summarising frequent event that happens during a user–specified period of time. The key idea that drives our solution is to proceed with the summarisation by steps, as it follows: (1) GPS Points: first of all we need to extract all the paths that the subject has done in the given period of time. With this data we can recognize the most frequent path; (2) People: from the paths it is possible to extract the people that the subject have encounter more times, in order to get the frequent person seen; and (3) Images: with the new information we can now get the most interesting pictures that can describe the place and the people seen in this period of time. The photos will be selected from the ones captured on the starting and arrival place and we use some criteria to choose which one is better.|