Understanding First-Person and Third-Person Videos in Computer Vision

Due to advancements in technology and social media, a large amount of visual information is created. There is a lot of interesting research going on in Computer Vision that takes into consideration either visual information generated by first-person (egocentric) or third-person(exocentric) cameras. Video data generated by YouTubers, Surveillance cameras, and Drones which is referred to as third-person or exocentric video data. Whereas first-person or egocentric is the one which is generated by GoPro cameras and Google Glass. Exocentric view capture wide and global views whereas egocentric view capture activities an actor is involved in w.r.t. objects. These two perspectives seem to be independent yet related. In Computer Vision, these two perspectives have been studied by various domains like Activity Recognition, Object Detection, Action Recognition, and Summarization independently. Their relationship and comparison are less discussed in the literature. This paper tries to bridge this gap by presenting a systematic study of first-person and third-person videos. Further, we implemented an algorithm to classify videos as first-person/third-person with the validation accuracy of 88.4% and an F1-score of 86.10% using the Charades dataset.

Role of Matrix Factorization Model in Collaborative Filtering Algorithm: A Survey

Recommendation Systems apply Information Retrieval techniques to select the online information relevant to a given user. Collaborative Filtering is currently most widely used approach to build Recommendation System. CF techniques uses the user behavior in form of user item ratings as their information source for prediction. There are major challenges like sparsity of rating matrix and growing nature of data which is faced by CF algorithms. These challenges are been well taken care by Matrix Factorization. In this paper we attempt to present an overview on the role of different MF model to address the challenges of CF algorithms, which can be served as a roadmap for research in this area.Comment: 8 pages, 1 figure in IJAFRC, Vol.1, Issue 12, December 201