Selectively Accessing Light Field Face Images over Information Centric Networking

Abstract

This paper explores the synergies between a Future Internet network-layer architecture based on Information Centric Networking (ICN), and the usage of Light Field Imaging. Central to this idea is the creation of a symbiotic relationship between content names as the base network information exchange mechanism, and advanced content analysis from the rich image representations obtained by Light Field Imaging. Our work increments the base ICN behavior of allowing endpoints to remotely request content to the network using only its name, and adds the capability of requesting specific aspects inside the content itself (e.g., a person's face in an image). In this work, the main functionalities and requirements associated to a solution combining ICN and Light Field Imaging for addressing video-surveillance scenarios are presented, leading to the conceptualization of the SeLF-ICN (Selectively Accessing Light Field Faces over Information Centric Networking) framework. A first prototype of the framework was developed and deployed allowing the evaluation of the concepts, with results showcasing the feasibility of the proposed solution.