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The {OD} Theory of {TOD}: The Use and Limitations of Temporal Information for Object Discovery |
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@InProceedings{sanders:OD-Theory:AAAI02,
author = {Brandon C.S. Sanders and Randal C. Nelson and Rahul Sukthankar},
title = {The {OD} Theory of {TOD}: The Use and Limitations of Temporal Information for Object Discovery},
booktitle = {Proc. 18th Nat'l Conf. on Artificial Intelligence {AAAI02}},
year = {2002},
address = {Edmonton, Alberta},
month = {jul # "~28--" aug # "~01"},
publisher = {{AAAI} Press},
pages = {777--784},
abstract = { We present the theory behind TOD (the Temporal Object
Discoverer), a novel unsupervised system that uses
only temporal information to discover objects across
image sequences acquired by any number of
uncalibrated cameras. The process is divided into
three phases: (1) Extraction of each pixel's
temporal signature, a partition of the pixel's
observations into sets that stem from different
objects; (2) Construction of a global schedule that
explains the signatures in terms of the lifetimes of
a set of quasi-static objects; (3) Mapping of each
pixel's observations to objects in the schedule
according to the pixel's temporal signature. Our
Global Scheduling (GSched) algorithm provably
constructs a valid and complete global schedule when
certain observability criteria are met. Our
Quasi-Static Labeling (QSL) algorithm uses the
schedule created by GSched to produce the
maximally-informative mapping of each pixel's
observations onto the objects they stem from. Using
GSched and QSL, TOD ignores distracting motion,
correctly deals with complicated occlusions, and
naturally groups observations across cameras. The
sets of 2D masks recovered are suitable for
unsupervised training and initialization of object
recognition and tracking systems.},
annote = { Introduces Quasi-static OD and the Quasi-staic Labeling
theorem and algorithm (QSL). },
}