Search results for "Clutter"
showing 10 items of 11 documents
Tracking Moving Objects With a Catadioptric Sensor Using Particle Filter
2011
International audience; Visual tracking in video sequences is a widely developed topic in computer vision applications. However, the emergence of panoramic vision using catadioptric sensors has created the need for new approaches in order to track an object in this type of images. Indeed the non-linear resolution and the geometric distortions due to the insertion of the mirror, make tracking in catadioptric images a very challenging task. This paper describes particle filter for tracking moving object over time using a catadioptric sensor. In this work different problems due to the specificities of the catadioptric systems such as geometry are considered. The obtained results demonstrate an…
Improved locally adaptive least-squares detection of differences in images
2007
We introduce a method for change detection under nonuniform changes of intensity using an improved least-squares method. A locally adaptive normalizing window is correlated with the two images, and a morphological postprocessing is then applied to isolate objects that have been added or removed from the scene. We use a modification of the least-squares solution to get rid of clutter caused by intensity changes that do not satisfy the model assumed for the least-squares solution.
NATO Advanced Research Workshop on Explosives Detection
2019
As of 2017, there are an estimated 100 million abandoned land mines littered across 61 countries. Following the wars in Afghanistan, Libya, Syria, Yemen, and Ukraine, there has been a rise in casualties due to the triggering of previously-abandoned explosive devices. The above institutions combined specialties to develop a remotely-operable, multisensor, robotic device for the detection of land mines, UXO (1), and IEDs (2). The robotic detection device uses novel subsurface radar with imaging and target classification to differentiate between threatening landmines and innocuous clutter. The expected outcome of this research is the creation of a multi-sensor system on a semi-autonomous vehic…
Randomized Rx For Target Detection
2018
This work tackles the target detection problem through the well-known global RX method. The RX method models the clutter as a multivariate Gaussian distribution, and has been extended to nonlinear distributions using kernel methods. While the kernel RX can cope with complex clutters, it requires a considerable amount of computational resources as the number of clutter pixels gets larger. Here we propose random Fourier features to approximate the Gaussian kernel in kernel RX and consequently our development keep the accuracy of the nonlinearity while reducing the computational cost which is now controlled by an hyperparameter. Results over both synthetic and real-world image target detection…
Selecting the Kth nearest-neighbour for clutter removal in spatial point processes through segmented regression models
2023
We consider the problem of feature detection, in the presence of clutter in spatial point processes. A previous study addresses the issue of the selection of the best nearest neighbour for clutter removal. We outline a simple workflow to automatically estimate the number of nearest neighbours by means of segmented regression models applied to an entropy measure of cluster separation. The method is suitable for a feature with clutter as two superimposed Poisson processes on any twodimensional space, including linear networks. We present simulations to illustrate the method and an application to the problem of seismic fault detection.
Classification of spatio-temporal point pattern in the presence of clutter using K-th nearest neighbour distances
2019
In a point process spatio-temporal framework, we consider the problem of features detection in the presence of clutters. We extend the methodology of Byers and Raftery (1998) to the spatio-temporal context by considering the properties of the K-th nearest-neighbour distances. We make use of the spatio-temporal distance based on the Euclidean norm where the temporal term is properly weighted. We show the form of the probability distributions of such K-th nearest-neighbour distance. A mixture distribution, whose parameters are estimated with an EM algorithm, is used to classify points into clutters or features. We assess the performance of the proposed approach with a simulation study, togeth…
High-overtone bulk acoustic resonator as passive ground penetrating RADAR cooperative targets
2013
International audience; RAdio-frequency Detection And Ranging instruments—RADARs—are widely used for applications aimed at measuring passive target velocity or ranging for various metrology applications such as ground position and localization. Within the context of using piezoelectric acoustic passive sensors as cooperative targets to RADARs probed through a radiofrequency link, this paper reports on investigating the compatibility of narrowband resonator architectures with the classical operation mode of wideband RADAR instruments. Since single mode resonators are hardly compatible due to the limited bandwidth of their spectrum, the investigation has been extended to High-overtone Bulk Ac…
Detection and Recognition of Target Signals in Radar Clutter via Adaptive CFAR Tests
2006
In this paper, adaptive CFAR tests are described which allow one to classify radar clutter into one of several major categories, including bird, weather, and target classes. These tests do not require the arbitrary selection of priors as in the Bayesian classifier. The decision rule of the recognition techniques is in the form of associating the p-dimensional vector of observations on the object with one of the m specific classes. When there is the possibility that the object does not belong to any of the m classes, then this object is to be classified as belonging to one of the m classes or to class m+1 whose distribution is unspecified. The tests are invariant to intensity changes in the …
Salient Spin Images: A Descriptor for 3D Object Recognition
2018
In the last decades a wide range of algorithms have been devoted to recognize 3D free-from objects under real conditions such as occlusions, clutters, rotation, scale and translation. Spin image is one of these algorithms known to be robust to rotation, translation, occlusions up to 70% and clutters up to 60%, but still suffer from scaling, resolution changes and it is time consuming. In this paper we present a novel approach based on spin images, called salient spin images (SSI). This method enhances spin images algorithm based on its limits. Particularly, it decreases significantly the complexity of the algorithm using DoG detector, it shows a higher performance due to the relevant locali…
Spatio‐temporal classification in point patterns under the presence of clutter
2019
We consider the problem of detection of features in the presence of clutter for spatio-temporal point patterns. In previous studies, related to the spatial context, Kth nearest-neighbor distances to classify points between clutter and features. In particular, a mixture of distributions whose parameters were estimated using an expectation-maximization algorithm. This paper extends this methodology to the spatio-temporal context by considering the properties of the spatio-temporal Kth nearest-neighbor distances. For this purpose, we make use of a couple of spatio-temporal distances, which are based on the Euclidean and the maximum norms. We show close forms for the probability distributions o…