Photo identity tag suggestion using only social network context on large-scale web services

Abstract

Recently, uploading photos and adding identity tags on social network services are prevalent. Although some researchers have considered leveraging context to facilitate the process of tagging, these approaches still rely mainly on face recognition techniques that use visual features of photos. However, since the computational and storage costs of these approaches are generally high, they cannot be directly applicable to largescale web services. To resolve this problem, we explore using only social network context to generate the top-k list of photo identity tag suggestion. The proposed method is based on various co-occurrence contexts that are related to the question of who may appear in this photo. An efficient ranking algorithm is designed to satisfy the real-time needs of this application. We utilize public album data of 400 volunteers from Facebook to verify that our approach can efficiently provide accurate suggestions with less additional storage requirement.

Improving face recognition with genealogical and contextual data

“…Shimizu et al's basic use of co-occurrence provides promising results, but requires manual confirmation of photograph relevance [45]. The use of context acquired solely from co-occurrence in photos within a social network, without any visual feature analysis, has provided good accuracy [15,18,47]; however these solutions are designed for use within a large scale online social network rather than in a personal collection. It also makes use of a great deal of contextual information that is not available in a genealogical application, such as who has made comments on a photo.…”

“…This is unlikely in historical family photos, with fewer photos being taken in the past. The use of identity co-occurrence within photo collections has been explored in many studies [45,15,11,52,27,35]. Shimizu et al's basic use of co-occurrence provides promising results, but requires manual confirmation of photograph relevance [45].…”