ECE Seminar: Natural Scene Recognition: From Humans to Computers

Title: Natural Scene Recognition: From Humans to Computers
Speaker: Prof. Fei-Fei Li
Date: October 10, 2007

Abstract:
For both humans and machines, the ability to learn and recognize the semantically meaningful contents of the visual world is an essential andimportant functionality. In this talk, we will examine the topic ofnatural scene categorization and recognition in human psychophysical and physiological experiments as well as in computer vision modeling.

I will first present a series of recent human psychophysics studies onnatural scene recognition. All these experiments converge to oneprominent phenomena of the human visual system: humans are extremely efficient and rapid in capturing the semantic contents of the real-worldimages. Inspired by these behavioral results, we report a recent fMRIexperiment that classifies different types of natural scenes (e.g. beach vs. building vs. forest, etc.) based on the distributed fMRI activity.This is achieved by utilizing a number of pattern recognition algorithmsin order to capture the multivariate nature of the complex fMRI data.

In the second half of the talk, we present a generative Bayesianhierarchical model that learns to categorize natural images in a weaklysupervised fashion. We represent an image by a collection of localregions, denoted as codewords obtained by unsupervised clustering. Eachregion is then represented as part of a `theme'. In previous work, suchthemes were learnt from hand-annotations of experts, while our method learns the theme distribution as well as the codewords distribution overthe themes without such supervision. We report excellent categorizationperformances on a large set of 13 categories of complex scenes.

Bio:Prof. Fei-Fei Li's main research interest is in vision, particularlyhigh-level visual recognition.
In computer vision, Fei-Fei's interestsspan from object and natural scene categorization to human activity categorizations in both videos and still images. In human vision, shehas studied the interaction of attention and natural scene and objectrecognition. In a recent project, she also studies the human brain fMRI activities in natural scene categorization by using pattern recognitionalgorithms. Fei-Fei graduated from Princeton University in 1999 with aphysics degree, and a minor in engineering physics. She received her PhD in electrical engineering from the California Institute of Technology in2005. Fei-Fei was on faculty in the Electrical and Computer EngineeringDept. at the University of Illinois Urbana-Champaign (UIUC) from Sept 2005 to Dec 2006. Starting Jan 2007, Fei-Fei is an Assistant Professorin the Computer Science Department at Princeton University. She alsoholds courtesy appointments in the Psychology Department and theNeuroscience Program at Princeton. She is a recipient of the 2006 Microsoft Research New Faculty Fellowship. (Fei-Fei publishes under thename L. Fei-Fei.)