Automatic Face Naming by Learning Discriminative Affinity Matrices From Weakly Labeled Images

0
1704
Automatic Face Naming by Learning Discriminative Affinity Matrices From Weakly Labeled Images

Automatic Face Naming by Learning Discriminative Affinity Matrices From Weakly Labeled Images

Abstract

Given a collection of images, where each image contains several faces
In this paper, we propose two new methods to effectively solve this problem by learning two discriminative affinity matrices from these weakly labeled images.
We first propose a new method called regularized low-rank representation by effectively utilizing weakly supervised information to learn a low-rank reconstruction coefficient matrix while exploring multiple subspace structures of the data.

In social networking websites (e.g., Facebook), photo sharing websites (e.g., Flickr)

and news websites (e.g., BBC), an image that contains multiple faces can be associated with a caption specifying who is in the picture.

For instance, multiple faces may appear in a news photo with a caption that briefly describes the news.

Moreover, in TV serials, movies, and news videos, the faces may also appear in a video clip with scripts.

In the literature, a few methods were developed for the face naming problem .

In this paper, we focus on automatically annotating faces in images based on the ambiguous supervision from the associated captions.

gives an illustration of the face-naming problem. Some preprocessing steps need to be conducted before performing face naming.

Learning Discriminative Affinity Matrices for Automatic Face Naming

In this section, we propose a new approach for automatic face naming with caption-based supervision.

we formally introduce the problem and definitions, followed by the introduction of our proposed approach.

Specifically, we learn two discriminative affinity matrices by effectively utilizing the ambiguous labels, and perform face naming based on the fused affinity matrix.

 we introduce our proposed approaches rLRR and ASML for obtaining the two affinity matrices respectively.

In the remainder of this paper, we use lowercase/uppercase letters in boldface to denote a vector/matrix (e.g., a denotes a vector and A denotes a matrix).