Discovering Meaning in the Visual World
Speaker: Fei-Fei Li , Assistant Professor, Princeton University
Date: May 23 2007
Time: 3:00PM to 4:00PM
Location: Star Seminar Room (32-D463)
Host: C. Mario Christoudias, Gerald Dalley, MIT CSAIL
Contact: C. Mario Christoudias, Gerald Dalley, 3-4278, 3-6095, cmch@csail.mit.edu, dalleyg@mit.edu
Relevant URL: When humans encounter images or videos of the visual world, our visual
system is capable of extracting a rich plethora of information in as
short as a single glance. A large portion of this information is related
to semantic meanings, such as objects, scenes and purposeful motions.
This ability still poses a large challenge to today's computer vision
algorithms. In this talk, we will introduce algorithms that perform such
high level visual recognition tasks as object, scene, event and human
motion categorization. Furthermore, we will attempt to achieve these
recognition tasks under various learning conditions that mimic the human
learning conditions, such as one-shot learning, unsupervised learning,
and incremental learning. In object categorization, we will show two
projects focusing on one-shot learning as well as incremental learning
of objects. We will also show a recent study of true 3D object
categorization. Beyond objects, we will introduce several studies on
scene and event categorization. Finally, we will finish the talk with a
study on unsupervised learning of human motion categories.
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