Detection of Aircrafts on a Collision Course using Spatio-Temporal HOG
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Feature detection and description constitute important steps of many computer vision applications such as object detection and panorama stitching. Since those steps are computationally heavy, they might occupy significant portion of the full operation. Alt ...
Detecting interest points is a key component of vision-based estimation algorithms, such as visual odometry or visual SLAM. Classically, interest point detection has been done with methods such as Harris, FAST, or DoG. Recently, better detectors have been ...
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
This paper presents a development of an open-source flight planning tool for Remotely Piloted Aircraft Systems (RPAS) that is dedicated to high-precision photogrammetric mapping. This tool contains planning functions that are usually available in professio ...
We introduce a complete parameterization of the family of two-dimensional steerable wavelets that are polar-separable in the Fourier domain under the constraint of self-reversibility. These wavelets are constructed by multiorder generalized Riesz transform ...
For economical and ecological reasons aircraft are required to become more efficient by reducing fuel consumption and CO2 emissions. One way to achieve these objectives is to decrease the weight of the aircraft structure. The reduction is, however, limi ...
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 ...
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 this paper we apply boosting to learn complex non-linear local visual feature representations, drawing inspiration from its successful application to visual object detection. The main goal of local feature descriptors is to distinctively repre- sent a s ...
We propose a method to compute scale invariant features in omnidirectional images. We present a formulation based on Riemannian geometry for the definition of differential operators on non-Euclidian manifolds that describe the mirror and lens structure in ...
Institute of Electrical and Electronics Engineers2012