En aquesta tesi s'estudien els mètodes de codificació d'imatges i seqüències de vídeo des del punt de vista de la forma en què el sistema visual humà percep i entén la informació visual. La rellevància d'aquest estudi ve ...

In this demo we present intAIRact, an online hand-based touchless interaction system. Interactions are based on easy-to-learn hand gestures, that combined with translations and rotations render a user friendly and highly ...

Commercial depth sensors represent an opportunity for automation of certain 3D production and analysis tasks. One way to overcome some of their inherent limitations is by capturing the same scene with several depth sensors ...

Temporal clustering of human motion into semantically meaningful behaviors is a challenging task. While unsupervised methods do well to some extent, the obtained clusters often lack a semantic interpretation. In this paper, ...

We present a morphological filter for lossless image subsampling for a given downsampling-upsampling strategy. This filter is applied in a multiresolution decomposition and results in a more efficient scheme for image ...

This paper deals with the use of some morphological tools for image and video coding. Mathematical morphology can be considered as a shape-oriented approach to signal processing, and some of its features make it very useful ...

This article presents a new approach to the problem of simultaneous tracking of several people in low-resolution sequences from multiple calibrated cameras. Redundancy among cameras is exploited to generate a discrete 3D ...

Illumination changes may lead to false foreground (FG) segmentation and tracking results. Most of the existing FG extraction algorithms obtain a background (BG) estimation from temporal statistical parameters. Such ...

This paper provides an alternative solution to the costly representation of multi-view video data, which can be used for both rendering and scene analyses. Initially, a new efficient Monte Carlo discrete surface ...

Hand-crafted features employed in classical generic instance segmentation methods have limited discriminative power to distinguish different objects in the scene, while Convolutional Neural Networks (CNNs) based semantic ...