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The 2015 edition of the International Symposium on Image and Signal Processing and Analysis (ISPA 2015) is the ninth in the series of biennial research meetings and it follows the successful ISPA 2013 meeting held in Trieste, Italy. ISPA 2015 is held in Zagreb, the capital city of the Republic of Croatia.
The 2015 9th International Symposium on Image and Signal Processing and Analysis (ISPA) is the result of the dedicated efforts of many volunteers from all over the word. All papers included in these proceedings are results of years of research made by scientists coming from many different countries. Without their contribution and commitment this Symposium would not have been possible. The Program...
Brand monitoring and reputation management are vital tasks in all modern business intelligence frameworks. However, recent related technologies rely mostly on the textual aspect of online content, in order to extract the underlying sentiment with respect to particular brands. In this work, we demonstrate the sentiment analysis method in the context of a brand monitoring framework, breaking the text-only...
In this paper, we address the problem of image tagging and we propose automatic methods for image tagging, using tensor decompositions. Tensors are a suitable way of mathematically representing multilink relations. Another, complementary structure that captures the aforementioned high-order relations is the hypergraph. More specifically, three different matrices are derived from the hypergraph, namely,...
Local binary pattern (LBP) descriptors have been popular in texture classification in recent years. They were introduced as descriptors of local image texture and their histograms are shown to be well performing texture features. In this paper we introduce two new LBP descriptors, αLBP and its improved variant IαLBP. We evaluate their performance in classification by comparing them with some of the...
Vehicle classification problem is one of challenges in Intelligent Transportation System (ITS). Numerous approaches have been submitted to handle this problem. Real time environment condition and limitation make it more intriguing. In this paper we focus on real time vehicle detection, feature extraction, and classification for multiple object using a single stationary camera. Even though numerous...
In this paper, we present an approach to the problem of aligning a Point Distribution Model onto the human body. The key idea of this paper is the clustering of the shape displacements into classes, in order to group the residual deformations in a coherent direction according to the image. We combine this approach by employing the implicitly encoded constraints and the double cascade pattern defined...
The low-level task of foreground-background segregation is an important foundation for many high-level computer vision tasks and has been intensively researched in the past. Nonetheless, unregulated environments usually impose challenging problems and often particular difficulties arise from real time requirements. In this paper we propose a new energy function to evaluate the spatial relations in...
Fisher Vectors have shown great capability for visual search. Their main drawback is their high dimensionality. We propose several methods to reduce the size of the Fisher Vectors by applying different preprocessing steps and dimension reduction techniques to SIFT descriptors. Also, we investigate the effects of PCA and DCT transforms employed on SIFT descriptors and the resulting improvement for...
Automatic detection of moving objects is an important task for aerial surveillance. It has been a popular and well-studied subject for the computer vision community, but is still a challenge. The method we introduce targets surveillance low-altitude mini and micro-UAVs. We take advantage of the inherent image motion on footage captured by such aerial vehicles. Our method confronts Optical Flow vectors...
Blurring and color cast are two of the most challenging problems for underwater imaging. The poor quality hinders the automatic segmentation or analysis of images. In this paper, we describe an image enhancement method to reduce the blurring and color cast of the underwater medium. It is a two-folded approach; First, a color correction algorithm is applied to correct the color cast and produce a natural...
An algorithm is developed for automated modeling of tubular blood vessel segments, based on their noisy 3D raster image. The approach is based on continuous-function approximation of binary skeleton lines extracted from thresholded multiscale vesselness images. The continuous centerline functions allow robust computation of tangent vectors, to define normal planes and 3D image cross-sections on those...
The present study aims at expanding the knowledge in the field of stent-graft behaviour in patients affected by thoracic aortic pathologies, imaged before and after thoracic endovascular aortic repair (TEVAR) with a 4D computed tomographic (CT) angiography that allows time-resolved image visualisation. We therefore developed an automatic tool to track the changes in distensibility and elongation experienced...
Detecting micro-emboli in the middle cerebral artery is a major challenge because these micro-emboli are related to the risk of stroke (cerebrovascular accident). Because micro-emboli are defined as High Intensity Transient Signals (HITS), their detection require the estimation of the blood flow background signal; i.e, the reference from which HITS have to be detected. In this paper, we propose an...
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