A Variational Framework for the Simultaneous Segmentation and Object Behavior Classification of Image Sequences
Publications associées (36)
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Object recognition is one of the most important problems in computer vision. However, visual recognition poses many challenges when tried to be reproduced by artificial systems. A main challenge is the problem of variability: objects can appear across huge ...
Visual scene recognition deals with the problem of automatically recognizing the high-level semantic concept describing a given image as a whole, such as the environment in which the scene is occurring (e.g. a mountain), or the event that is taking place ( ...
Localization and context interpretation are two key competences for mobile robot systems. Visual place recognition, as opposed to purely geometrical models, holds promise of higher flexibility and association of semantics to the model. Ideally, a place rec ...
Visual behavior recognition is currently a highly active research area. This is due both to the scientific challenge posed by the complexity of the task, and to the growing interest in its applications, such as automated visual surveillance, human-computer ...
Visual scene recognition deals with the problem of automatically recognizing the high-level semantic concept describing a given image as a whole, such as the environment in which the scene is occurring (e.g. a mountain), or the event that is taking place ( ...
École Polytechnique Fédérale de Lausanne (EPFL)2014
Background: Automated segmentation of brain structures is an important task in structural and functional image analysis. We developed a fast and accurate method for the striatum segmentation using deep convolutional neural networks (CNN). New method: T1 ma ...
Over the past few decades we have been experiencing a data explosion; massive amounts of data are increasingly collected and multimedia databases, such as YouTube and Flickr, are rapidly expanding. At the same time rapid technological advancements in mobil ...
In this paper, we propose a general framework for fusing bottom-up segmentation with top-down object behavior inference over an image sequence. This approach is beneficial for both tasks, since it enables them to cooperate so that knowledge relevant to eac ...
We present MBIS (Multivariate Bayesian Image Segmentation tool), a clustering tool based on the mixture of multivariate normal distributions model. MBIS supports multichannel bias field correction based on a B-spline model. A second methodological novelty ...
With widening interests in using model organisms for reverse genetic approaches and biomimmetic micro-robotics, motility phenotyping of the nematode Caenorhabditis elegans is expanding across a growing array of locomotive environments. One ongoing bottlene ...