Vision-Based Unmanned Aerial Vehicle Detection and Tracking for Sense and Avoid Systems
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The sliding window approach is the most widely used technique to detect objects from an image. In the past few years, classifiers have been improved in many ways to increase the scanning speed. Apart from the classifier design (such as the cascade), the sc ...
Many classes of objects can now be successfully detected with statistical machine learning techniques. Faces, cars and pedestrians, have all been detected with low error rates by learning their appearance in a highly generic manner from extensive training ...
Speaker verification (SV) on portable devices like smartphones is gradually becoming popular. In this context, two issues need to be considered: 1) such devices have relatively limited computation resources, and 2) they are liable to be used everywhere, po ...
Latent variable models provide valuable compact representations for learning and inference in many computer vision tasks. However, most existing models cannot directly encode prior knowledge about the specific problem at hand. In this paper, we introduce a ...
The sliding window approach is the most widely used technique to detect objects from an image. In the past few years, classifiers have been improved in many ways to increase the scanning speed. Apart from the classifier design (such as the cascade), the sc ...
In laser micro-manufacturing, one of the challenges is to achieve fast scanning speed for fast fabrication of complex 3D microstructures. For microstructures with nanoscale features, it is often desirable to steer laser beams from a few microns to a few te ...
In this paper we present a method for real-time detection of human fall from video for support of elderly people living alone in their homes. The detection algorithm has four steps: background estimation, extraction of moving objects, motion feature extrac ...
Speaker verification on portable devices like smartphones is gradually becoming popular. In this context, two issues need to be considered: 1) such devices have relatively limited computation resources, and 2) they are liable to be used everywhere, possibl ...
Object classification and detection aim at recognizing and localizing objects in real-world images. They are fundamental computer vision problems and a prerequisite for full scene understanding. Their difficulty lies in the large number of possible object ...
Programme doctoral en Informatique, Communications et Information2013
We present a novel approach to automatic macroaction discovery and its application to a complex goal-planning task. The problem of macro-action discovery is framed as one of multiple change point detection and is addressed with the help of the Dynamic Prog ...