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Erschienen in:
2018 | OriginalPaper | Buchkapitel
Distributed Estimation of Vector Fields
verfasst von : Ana Portêlo, Jorge S. Marques, Catarina Barata, João M. Lemos
Erschienen in: Advanced Concepts for Intelligent Vision Systems
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Abstract
In many surveillance applications the area of interest is either wide or includes alleys or corners. Thus, the images from multiple cameras need to be combined and this fact motivates the use of distributed optimization approaches. This work proposes three distributed estimation approaches to motion field estimation from target trajectory data: (1) purely decentralized, without communication, (2) distributed estimation based on a cooperative game, and (3) distributed Alternating Direction Method of Multipliers (ADMM). Their performance in estimating different classes of motion fields is important to select the best approach for each application. Experiments using synthetic and real data show that (a) the cooperative game approach is very susceptible to changes in motion direction, and (b) the distributed ADMM approach is the most robust and reliable approach to estimate changing direction motion fields.