Machine Learning and Large-Scale Data for Visual Recognition

Abstract

For the automatic visual recognition, the semantic gap is the long lasting problem. Recently, by using the internet and the crowd sourcing services, the high quality annotated image datasets have been developed. To maximally utilize the high quality datasets, the strong computational power, and the efficient machine learning methods, the visual recognition system is showing signs of overcoming the semantic gap. In this paper, we overview and explain the recent development of the machine learning and the datasets for the visual recognition.