This was a part of research projects conducted under the Basic Research Laboratory Grant from Ministry of Education, Science, and Technology in South Korea. This project is two folds: (1) simulating an application of swarm robot systems; (2) designing a software framework for the swarm robot systems to reduce the complexity of developing applications while minimizing the amount of tranismitted data by adopting MapReduce paradigm. The video above is a simulation of a swarm robot system applicatoin that searches for red pillars (foraging).
This project was conducted in 2008 for my bachelor's thesis in the department of Electrical Engineering at Seoul National University (it was more like a capston project rather than a thesis, since the focus of the project was mainly at implementing algorithms rather than analyzing the performance of algorithms using concrete measures, e.g., recall and precision). I implemented an image retrieval system prototype that takes an image as input, and outputs most similar images from the image database.
Hao Li (Ph.D. student from CS) and I conducted a big-data analysis project using the MapReduce framework (Hadoop) for the final project of INFM718G (Data-Intensive Computing with MapReduce, by Dr. Jimmy Lin). Targeting all the news images in April 2013, we tried to rank news images based on the imporance and popularity level of each news image. In order to do that, we extracted image features using SIFT (Scale-invariant feature transform) and constructred a graph of images using LSH (Locality-sensitive Hashing) as a means to approximate the simliarity of images.