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Hyperspectral anomaly detection has been the subject of increased attention in the past 20 years. One obvious trend for scholars is seeking an appropriate data description in the hyperspectral anomaly detection domain. However, a specific predetermined data model in a given detector may not be able to fit all the other cases of hyperspectral images. Hence, can we construct a hyperspectral anomaly...
To solve the problem that there is few invariant features, which can be extracted from both images, to be matched for large changes of view, an efficient invariant image matching approach is presented. The proposed approach consists of two main steps. In the first step, we use the multi-resolution strategy to detect maximally stable extremal regions (MSERs) and obtain the geometric transformation...
Speed Up Robust Features SURF is one of the most popular and efficient methods used for image registration task. In order to achieve a correct registration, a good matching of feature point is required. However in the case of multimodal images, the high and non-linear intensity changes between different modalities led to many outliers (mismatching of detected points) and consequently a fail in the...
With the growing of available large datasets for evaluation, face detection in recent literature has progressed rapidly. However, little research has been dedicated to develop a face detector robust to all possible variations. To address this problem, novel unconstrained datasets containing faces with more challenging variations are proposed. We notice that some recent face detectors have not been...
This paper addresses the problem of person re-identification and its application to a real world scenario. We introduce a retrieval system that helps a human operator in browsing a video content. This system is designed for determining whether a given person of interest has already appeared over a network of cameras. In contrast to most of state of the art approaches we do not focus on searching the...
Semiparametric detection consists of combining the statistical optimality of a parametric test to the robustness regarding the data of a nonparametric test. This approach is specially interesting in presence of statistical hypotheses depending on unknown probability distributions. The proposed semiparametric approach consists of splitting the measurement vector into two parts such that the first part...
Finding corresponding image points is a challenging computer vision problem, especially for confusing scenes with surfaces of low textures or repeated patterns. Despite the well-known challenges of extracting conceptually meaningful high-level matching primitives, many recent works describe high-level image features such as edge groups, lines and regions, which are more distinctive than traditional...
We are focused on how to describe a common image point distinctively, make its descriptor concise and invariant to general image transformations. We use neighborhood pixel characteristics, including HSV color space, Gaussian-weighted gradient magnitudes and orientations, sampled in specific window around interest point to enhance the description. The enhanced point descriptor (EPD) is a covariance...
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