Labeling persons appearing in video frames with names detected in a corresponding video transcript helps improving video content annotation and search tasks. We implement a face naming method that learns from labeled and unlabeled examples using iterative label propagation in a graph of connected faces or name-face pairs. By incorporating the unlabeled data points during the learning process, this method can work with few labeled data points. Moreover, we present variations of this model that better cope with a large number of data by reducing the time and space complexity. On BBC News videos, the label propagation algorithm yields better results than a Support Vector Machine classifier and a nearest neighbor classifier trained on the same ...
International audienceTV archives are growing in size so fast that manually indexing becomes unfeasi...
International audienceTV archives are growing in size so fast that manually indexing becomes unfeasi...
International audienceTV archives are growing in size so fast that manually indexing becomes unfeasi...
Recently, there is a strong demand for making use of large amounts of video data efficiently and eff...
It is very desirable for media users to know the names of people in videos. Naming persons who are a...
Recognizing the identity of a face or a person in the media usually requires lots of training data t...
We present a method for automatically labelling all faces in video archives, such as TV broadcasts, ...
In this paper, we focus on the problem of automated video annotation. We report on the application o...
We have been developing Name-It, a system that associates faces and names in news videos. First, as ...
We have been developing Name-It, a system that associates faces and names in news videos. First, as ...
International audienceTV archives are growing in size so fast that manually indexing becomes unfeasi...
International audienceTV archives are growing in size so fast that manually indexing becomes unfeasi...
International audienceTV archives are growing in size so fast that manually indexing becomes unfeasi...
International audienceTV archives are growing in size so fast that manually indexing becomes unfeasi...
International audienceTV archives are growing in size so fast that manually indexing becomes unfeasi...
International audienceTV archives are growing in size so fast that manually indexing becomes unfeasi...
International audienceTV archives are growing in size so fast that manually indexing becomes unfeasi...
International audienceTV archives are growing in size so fast that manually indexing becomes unfeasi...
Recently, there is a strong demand for making use of large amounts of video data efficiently and eff...
It is very desirable for media users to know the names of people in videos. Naming persons who are a...
Recognizing the identity of a face or a person in the media usually requires lots of training data t...
We present a method for automatically labelling all faces in video archives, such as TV broadcasts, ...
In this paper, we focus on the problem of automated video annotation. We report on the application o...
We have been developing Name-It, a system that associates faces and names in news videos. First, as ...
We have been developing Name-It, a system that associates faces and names in news videos. First, as ...
International audienceTV archives are growing in size so fast that manually indexing becomes unfeasi...
International audienceTV archives are growing in size so fast that manually indexing becomes unfeasi...
International audienceTV archives are growing in size so fast that manually indexing becomes unfeasi...
International audienceTV archives are growing in size so fast that manually indexing becomes unfeasi...
International audienceTV archives are growing in size so fast that manually indexing becomes unfeasi...
International audienceTV archives are growing in size so fast that manually indexing becomes unfeasi...
International audienceTV archives are growing in size so fast that manually indexing becomes unfeasi...
International audienceTV archives are growing in size so fast that manually indexing becomes unfeasi...