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[B] [M] Visual place recognition under image corruptions

BACHELOR Assignment

Visual place recognition under image corruptions

Type: Bachelor EE/CS/HMI

Period: TBD

Student: (Unassigned)

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Visual place recognition has received large interest from  researchers in computer vision, machine learning and information retrieval. It consists of, given a query image, seeking an image depicting a similar scene in a map or database. Possible instances of this problem are the retrieval of an image containing a specific distinctive landmark (e.g. monument recognition) or the recognition of a previously visited place for robot navigation or autonomous driving. State-of-the-art algorithms for place recognition deploy convolutional neural networks, which suffer from lack of robustness when the input images are subject to corruptions as shown in [1] on the task of image classification.


The objective of the project is to study the robustness of convolutional networks for place recognition, with special focus on siamese architectures [2], when the input images are subject to common corruptions and perturbations in computer vision (e.g. noise, motion blur, zoom blur, jpeg compression, contrast, etc.).