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We study the question of feature sets for robust visual object recognition; adopting linear SVM based human detection as a test case. After reviewing existing edge and gradient based descriptors, we show experimentally that grids of histograms of oriented gradient (HOG) descriptors significantly outperform existing feature sets for human detection. We study(More)
Detecting humans in films and videos is a challenging problem owing to the motion of the subjects, the camera and the background and to variations in pose, appearance, clothing, illumination and background clutter. We develop a detector for standing and moving people in videos with possibly moving cameras and backgrounds, testing several different motion(More)
This thesis targets the detection of humans and other object classes in images and videos. Our focus is on developing robust feature extraction algorithms that encode image regions as highdimensional feature vectors that support high accuracy object/non-object decisions. To test our feature sets we adopt a relatively simple learning framework that uses(More)
The PASCAL Visual Object Classes Challenge ran from February to March 2005. The goal of the challenge was to recognize objects from a number of visual object classes in realistic scenes (i.e. not pre-segmented objects). Four object classes were selected: motorbikes, bicycles, cars and people. Twelve teams entered the challenge. In this chapter we provide(More)
In this paper we describe a method for analysing video sequences and for representing them as mosaics or panoramas. Previous work on video mosaicking essentially concentrated on static scenes. We generalise these approaches to the case of a rotating camera observing both static and moving objects where the static portions of the scene are not necessarily(More)
This paper proposes a robust estimation and validation framework for characterizing local structures in a positive multi-variate continuous function approximated by a Gaussian-based model. The new solution is robust against data with large deviations from the model and margin-truncations induced by neighboring structures. To this goal, it unifies robust(More)
Given two or more video sequences containing similar human activities (running, jumping, etc.) we want to devise a method which extracts spatio-temporal signatures associated with these activities, compares these signatures, and aligns key positions of different videos. In this paper we introduce a method which, in conjunction with a number of hypotheses,(More)
View interpolation has been explored in the scientific community as a means to avoid the complexity of full 3D in the construction of photo-realistic interactive scenarios. EVENTS project attempts to apply state of the art view interpolation to the field of professional sports. The aim is to populate a wide scenario such as a stadium with a number of(More)
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