Results 251 to 260 of about 2,759,993 (296)

Selecting and tracking multiple objects

WIREs Cognitive Science, 2014
When interacting with the world, people can dynamically split attention across multiple objects in the environment, both when the objects are stationary and when the objects are moving. This type of visual processing is commonly studied in lab settings using either static selection tasks or moving tracking tasks. We describe performance limits that are
Jason M. Scimeca, Steven L. Franconeri
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Multiple Object Motions

1992
Up to now, we have been interested in the motion analysis of two frames in which there is only one moving object. In other words, we can solve the following two problems:
Zhengyou Zhang, Olivier Faugeras
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Multiple Objective Optimization

2020
In this chapter, we discuss the differences between a MOOP and a SOOP and present the weighted sum approach and the e-constraint method to solve convex MOOPs formulated as multi-objective linear optimization problems (MOLPs). Moreover, we highlight the fundamental principles of multi-objective optimization and present a way to explore the Pareto ...
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Multiple Object Spectroscopy

1988
We review current techniques for multiple object spectroscopy and discuss the new automated fibre positioner, AUTOFIB, recently commissioned on the AAT. We contrast the advantages and disadvantages of fibre optic couplers and multislit devices, especially at faint limits. Fibres offer large multiplex gains but spatial fluctuations in the sky background
Ellis, Richard S., Parry, Ian R.
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MULTIPLE OBJECT TRACKING WITH RELATIONS

Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods, 2012
Dealing with multi-object tracking raises several issues; an essential point is to model possible interactions between objects. Indeed, while reliable algorithms for tracking multiple non-interacting objects in constrained scenarios exist, tracking of multiple interacting objects in uncontrolled scenarios is still a challenge.
CATTELANI, LUCA, MANFREDOTTI, CRISTINA ELENA, MESSINA, VINCENZINA   +2 more
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Robust Multiple Objective Game Theory

Journal of Optimization Theory and Applications, 2012
This paper deals with the problem of robust multiple objective games. For incomplete information multiple objective games, it is assumed that the players cannot evaluate the possible values and distributional information of the uncertain payoff parameters accurately, but only know these parameters belong to an uncertainty set.
Yu, H., Liu, H. M.
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Multiple Objective Linear Fractional Programming

Management Science, 1981
This paper presents a simplex-based solution procedure for the multiple objective linear fractional programming problem. By (1) departing slightly from the traditional notion of efficiency and (2) augmenting the feasible region as in goal programming, the solution procedure solves for all weakly efficient vertices of the augmented feasible region. The
Jonathan S. H. Kornbluth, Ralph E. Steuer   +1 more
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Stationary objects in multiple object tracking

2007 IEEE Conference on Advanced Video and Signal Based Surveillance, 2007
This paper presents an approach to detect stationary foreground objects in naturally busy surveillance video scenes with several moving objects. Our approach is inspired by human's visual cognition processes and builds upon a multi-tier video tracking paradigm with main layers being the spatially based "peripheral tracking" loosely corresponding to the
Sadiye Guler, Jason A. Silverstein, Ian H. Pushee   +2 more
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A multiple‐objective dispersion problem

Journal of Multi-Criteria Decision Analysis, 1995
AbstractIn this paper we study a multiple‐objective dispersion problem from an efficient solution and value function perspective. A general fundamental theorem on non‐dominance is given and a polar co‐ordinate elimination heuristic is given for the case of R2.
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Fuzzy Multiple Objective Decision Making

2011
The fuzzy programming approach [194, 410, 412] is useful and efficient for treating a programming problem under uncertainty. While a classical and stochastic programming approach may cost a lot to obtain the exact coefficient value or distribution, fuzzy programming approach does not [411].
Jiuping Xu, Xiaoyang Zhou
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