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In this work a new method for automatic image classification is proposed. It relies on a compact representation of images using sets of sparse binary features. This work first evaluates the Fast Retina Keypoint binary descriptor and proposes imp ...
A large part of computer vision research is devoted to building models
and algorithms aimed at understanding human appearance and behaviour
from images and videos. Ultimately, we want to build automated systems
that are at least as capable as people when i ...
In this paper we propose a pixel-wise visual tracking method using a novel tri-model representation. The newly proposed tri-model is composed of three models, which each model learns the target object, the background, and other non-target moving objects on ...
Polynomial Networks (PNs) have demonstrated promising performance on face and image recognition recently. However, robustness of PNs is unclear and thus obtaining certificates becomes imperative for enabling their adoption in real-world applications. Exist ...
In this thesis, I focus on monitoring of patients suffering from cardiovascular and neurological diseases through the use of wearable devices. The main diseases considered in this thesis are atrial fibrillation (AF), myocardial infarction (MI), and epileps ...
The study of newspaper layout evolution through historical corpora has been addressed by diverse qualitative and quantitative methods in the past few years. The recent availability of large corpora of newspapers is now making the quantitative analysis of l ...
A crucial feature of a good scene recognition algorithm is its ability to generalize. Scene categories, especially those related to human made indoor places or to human activities like sports, do present a high degree of intra-class variability, which in t ...
Detection of elongated structures in 2D images and 3D image stacks is a critical prerequisite in many applications and Machine Learning-based approaches have recently been shown to deliver superior performance. However, these methods essentially classify i ...
With the technological evolution of digital acquisition and storage technologies, millions of images and video sequences are captured every day and shared in online services. One way of exploring this huge volume of images and videos is through searching a ...
This study proposes a new robust classifier for sit-to-stand (SiSt) and stand-to-sit (StSt) detection in daily activity. The monitoring system consists of a single inertial sensor placed on the trunk. By using dynamic time warping, the trunk acceleration p ...
Institute of Electrical and Electronics Engineers2012
