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We present a novel data set made up of omnidirectional video of multiple objects whose centroid positions are annotated automatically. Omnidirectional vision is an active field of research focused on the use of spherical imagery in video analysis and scene understanding, involving tasks such as object detection, tracking and recognition. Our goal is to provide a large and consistently annotated video...
Accurate vessel segmentation is a tough task for various medical images applications especially the segmentation of retinal images vessels. A computerised algorithm is required for analysing the progress of eye diseases. A variety of computerised retinal segmentation methods have been proposed but almost all methods to date show low sensitivity for narrowly low contrast vessels. We propose a new retinal...
This paper proposes a new pylon detection technique from point cloud data. Two masks are created from the non-ground points that mainly represent trees and power line components. The first mask is the power line mask Mₘ, which contains the power line components and trees and where successive pylons are found connected with wires. The second mask is the pylon mask Mₚ, where successive pylons are found...
Skin segmentation, which involves detecting human skin areas in an image, is an important process for skin disease analysis. The aim of this paper is to identify the skin regions in a newly collected set of psoriasis images. For this purpose, we present a committee of machine learning (ML) classifiers. A psoriasis training set is first collected by using pixel values in five different color spaces...
Convolutional neural network (CNN) based trackers have achieved significant performances in tracking recently. Most existing CNN-based trackers regard tracking as a classification or similarity searching problem. The two methods have their respective superiorities and limitations because of different supervised objectives. In this paper, we propose a multi-task CNN for visual tracking, not only fully...
The popularly used subjective estimator- mean opinion score (MOS) is often biased by the testing environment, viewers mode, domain expertise, and many other factors that may actively influence on actual assessment. We therefore, devise a no- reference subjective quality assessment metric by exploiting the nature of human eye browsing on videos. The participants' eye-tracker recorded gaze-data indicate...
Cancerous masses detection in dense background is a particularly challenging task for even experienced radiologists due to their similarity of intensity with the overlapped normal dense tissues, obscured boundaries and low contrast between mass and surrounding regions. This paper proposes a novel approach for the identification of cancerous regions located in a dense part of a breast. Careful analysis...
Recent research in tomographic reconstruction is motivated by the need to efficiently recover detailed anatomy from limited measurements. One of the ways to compensate for the increasingly sparse sets of measurements is to exploit the information from \emph{templates}, i.e., prior data available in the form of already reconstructed, structurally similar images. Towards this, previous work has exploited...
This paper suggests a new method for image registration, based on a new similarity measure, the standard deviation normalized summed squared difference. Such a similarity measure is explicitly defined on the effective overlap between two images, and the image registration is fulfilled by searching for a global minimum peak of this measure over the entire parameter space. Conceptually the suggested...
This study proposes a method for analysis and calibration of the geo-coding error in mapping of the moving targets, 'movers', detected in the Wide Area Motion Imagery (WAMI). To estimate the accurate position of the movers, an iterative Ordinary Least Squares (OLS) optimisation of the camera model parameters is performed. The OLS is set to minimise the Euclidean distance between the locations of the...
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