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GRASP Special Seminar: Anthony Hoogs, Kitware, Inc., “Persistent, Wide-Area Video Analytics at Big Data Scales”

April 22, 2014 @ 2:00 pm - 3:00 pm

Abstract: The scale of video data
continues to grow exponentially, including city-scale wide-area
aerial video showing hundreds or thousands of simultaneous movers.
Extracting the most interesting, salient content from this type of
video is of increasing importance as the data volume grows while
the vast majority of events are not of interest. However,
traditional methods often fail because of low resolution and low
frame rates in this domain. At Kitware we have developed methods
for detecting events, actions, complex activities, patterns of
life and anomalies in large-scale video domains. We detect events,
anomalies and complex activities efficiently by detecting and
tracking all movers, then characterizing their behavior using
event-independent descriptors. Efficient inference is achieved
through layered, approximate evaluation as model complexity
increases. Functional scene elements such as parking spots are
recognized by analyzing behavior within and around them.
Behavioral normalcy models are learned, and anomalies are detected
using location-dependent and location-independent techniques. The
talk will provide an overview of these methods and results on
wide-area and ground-level surveillance video.


- Learn More

Dr. Anthony Hoogs is the Senior Director of
Computer Vision at Kitware, a small software R&D firm based on
open source. Dr. Hoogs joined Kitware in August 2007 and founded
the Computer Vision group, which now has 25 members including 12
PhDs. He has initiated and led more than two dozen contracts in
video and motion analysis, involving more than 15 universities
including the University of Pennsylvania. At GE Global Research
(1998-2007), Dr. Hoogs led a team of researchers in video and
imagery analysis on projects sponsored by the US Government,
Lockheed Martin and NBC Universal. For more than two decades, he
has supervised and performed research in various areas of computer
vision including: event, activity and behavior recognition; motion
pattern learning and anomaly detection; tracking; visual
semantics; image segmentation; object recognition; and
content-based retrieval. He has published more than 70 papers in
computer vision, has served as Workshops Chair, Corporate
Relations Chair and Area Chair for CVPR, and is on the steering
committee for the Winter conference on Applications of Computer
Vision (WACV). Dr. Hoogs received a Ph.D. in Computer and
Information Science from the University of Pennsylvania in 1998,
in the GRASP Lab under Dr. Ruzena Bajcsy; an M.S. from the
University of Illinois at Urbana-Champaign in 1991; and a B.A.
from Amherst College in 1989.


April 22, 2014
2:00 pm - 3:00 pm
Event Category: