English
导航菜单
Recent Advances in Online Object
Tracking
时间： 2013年6月9日(星期日，端午节前工作日)
10:00~12:00
地点： 电信群楼5号楼406
报告人：Ming-Hsuan
Yang
Abstract: There has been a growing interest in compressive sensing and sparse
representation in the past few years. In this talk, Professor Yang will present
some recent newest results on how these theories can be extended and applied
for constructing effective appearance models within the context of online
object tracking.
First, Prof. Yang will present
the recent results on compressive tracking. The proposed appearance model
employs non-adaptive random projections which preserve the structure of image
feature space. A sparse measurement matrix is adopted to efficiently compress
the features in a low-dimensional space for foreground and background
separation, thereby facilitating real-time object tracking.
Second, Prof. Yang will present a
collaborative model for object tracking in which they exploit both holistic
templates and local representations. They develop a sparsity-based
discriminative classifier and a sparsity-based generative model. Within their
tracking scheme, the collaboration of generative models and discriminative
classifiers contributes to achieve more robust results.
Finally, while much progress has
been made in recent years with efforts to share code and data sets, it is of
great importance to develop a library and benchmark to gauge the state of the
art. He will present some of their findings on large scale experiments with
different evaluation criteria to understand how these algorithms perform. These
findings also reveal critical components for a robust tracker for future
research.
Biography: Ming-Hsuan Yang is an assistant professor in Electrical Engineering and
Computer Science at University of California, Merced. He received the PhD
degree in Computer Science from the University of Illinois at Urbana-Champaign
in 2000. He has served as an area chair for several conferences including IEEE
Conference on Computer Vision and Pattern Recognition, IEEE International
Conference on Computer Vision, Asian Conference on Computer Vision, AAAI
National Conference on Artificial Intelligence, and IEEE International
Conference on Automatic Face and Gesture Recognition. He served as an associate
editor of the IEEE Transactions on Pattern Analysis and Machine Intelligence
from 2007 to 2011, and currently is as an associate editor of the Image and
Vision Computing. Yang received the Google Faculty Award in 2009, and the
Distinguished Early Career Research award from the UC Merced senate in 2011.
Yang is a recipient of the Faculty Early Career Development (CAREER) award from
the National Science Foundation in 2012. He is a senior member of the IEEE and
the ACM.
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