People-LDA: Anchoring Topics to People using Face Recognition

This page is intended to display more results which could not be accomodated in the following paper due to space constraints. We also intend to share the code for the model proposed in our paper:

Vidit Jain, Erik Learned-Miller, Andrew McCallum.

People-LDA: Anchoring Topics to People using Face Recognition.

International Conference on Computer Vision (ICCV), 2007, Rio De Janeiro, Brazil.

Good cluster examples

Noisy cluster examples

Examples of good people-topics and corresponding distributions of words

Note that some clusters have more than one people that are similar to each other visually (see Kofi Annan's topic) or through some underlying theme of the topic (Parvez Musharraf and Benazir Bhutto in Parvez Musharraf's topic).

	aniston los angeles hollywood actress jennifer emmy awards annual series		security homeland department ridge washington police director tom reporters john
	annan williams general kofi chief secretary nations file iraq blix		musharraf conference general pakistan pervez north islamabad korea war bhutto
	united states iraq mahathir photo general told mohamad attack inspectors		daschle leader senate tom majority bush white house lott trent

Examples of noisy clusters and corresponding distributions of words

Note that some topics did not emerge around people but represent a group (tennis, in the top-left topic), or contain many face images of a different person with a similar appearance (Jennifer Aniston in the Britney Spears' topic and Vladimir Putin in the Igor Ivanov's topic).

	tournament returns match tennis won hewitt blake masters australia ball		seen file ring arrives shown photo charged case step store
	spears film city star premiere poses britney watts mexico week		open york states sampras flushing united agassi defeated gambill set
	bush ivanov house media white igor meeting defense russian george		weapons blix iraq resolution nations council united inspector inspectors chief