Ensuring Quality of Experience for markerless image recognition applied to print media content

Abstract

This paper investigates how minimal user interaction paradigms and markerless image recognition technologies can be applied to matching print media content to online digital proofs. By linking print material to online content, users can enhance their experience with traditional forms of print media with updated online content, videos, interactive online features etc. The proposed approach is based on extracting features from images/text from mobile device camera images to form `fingerprints' that are used to find matching images/text within a limited test set. An important criterion for these applications is to ensure that the user Quality of Experience (QoE), particularly in terms of matching accuracy and time, is robust to a variety of conditions typically encountered in practical scenarios. In this paper, the performance of a number of computer vision techniques that extract the image features and form the fingerprints are analysed and compared. Both computer simulation tests and mobile device experiments in realistic user conditions are conducted to study the effectiveness of the techniques when considering scale, rotation, blur and lighting variations typically encountered by a user.