Models for computer vision are commonly defined either wrt low-level concepts such as
pixels that are to be grouped, or wrt high-level concepts such as semantic objects that are to …

Humans easily recognize object parts and their hierarchical structure by watching how they
move; they can then predict how each part moves in the future. In this paper, we propose a …

In this paper, we propose a novel rigid-body motion segmentation algorithm that uses
randomized voting to assign high scores to correctly estimated models and low scores to …

We propose a hierarchical method for learning temporal structures for the recognition of
complex human activities or actions in videos. Low level features (HOG, HOF, MBH x and …

Landmarks and keypoints are an important intermediate representation for image
understanding and reconstruction. Although, many supervised approaches exist, these …

Our thesis research is concerned with the estimation of motion saliency in image sequences.
First, we have defined an original method to detect frames in which a salient motion is …

Human action recognition from videos plays a crucial role in applications such as video
annotation and retrieval, intelligent surveillance, sports video analysis, human-computer …