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To go beyond the query-by-example paradigm in image retrieval, there is a need for semantic indexing of large image collections for intuitive text-based image search. Different models have been proposed to learn the dependencies between the visual content ...
The ever increasing number of digital images in both public and private collections urges on the need for generic image content analysis systems. These systems need to be capable to capture the content of images from both scenes and objects, in a compact w ...
The ever increasing number of digital images in both public and private collections urges on the need for generic image content analysis systems. These systems need to be capable to capture the content of images from both scenes and objects, in a compact w ...
The approach to indexing an image collection depends on the type of data to organize. Satellite images are likely to be searched with latitude and longitude coordinates, medical images are often searched with an image example that serves as a visual query, ...
The approach to indexing an image collection depends on the type of data to organize. Satellite images are likely to be searched with latitude and longitude coordinates, medical images are often searched with an image example that serves as a visual query, ...
This paper explores the issue of interactive low-dimensional human motion synthesis. We compare the performances of two motion models, i.e. Principal Components Analysis (PCA) or Probabilistic PCA (PPCA), for solving a constrained optimization problem with ...
The approach to indexing an image collection depends on the type of data to organize. Satellite images are likely to be searched with latitude and longitude coordinates, medical images are often searched with an image example that serves as a visual query, ...
We present an approach to teach incrementally human gestures to a humanoid robot. The learning process consists of first projecting the movement data in a latent space and encoding the resulting signals in a Gaussian Mixture Model (GMM). We compare the per ...
We present a framework to automatically discover people's routines from information extracted by cell phones. The framework is built from a probabilistic topic model learned on novel bag type representations of activity-related cues (location, proximity an ...
This paper presents a novel approach for visual scene modeling and classification, investigating the combined use of text modeling methods and local invariant features. Our work attempts to elucidate (1) whether a text-like \emph{bag-of-visterms} represent ...
