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A method for detecting dominant points on a 3-D digital curve is presented. The essential point is how accurately local properties such as curvatures and tangent vectors at every point are computed. This procedure first computes temporary properties by line or circle approximation using k-neighbors, then determines the optimum approximation by comparing the error value and correcting properties, and...
Thanks to the advances of data acquisition techniques, we can acquire ventricular blood flow data with very high quality. This extremely complex spatiotemporal data calls for novel visualization and analysis tools. In particular, the new tools need to assist domain experts in quick identification of critical patterns. In this paper, we present a method using topo-logical data analysis tools with simulated...
Banknotes, known as a bill, paper money, or simply a note, may be shredded by a scrap machine, ripped up by hand, or damaged in accidents. To assemble broken money note pieces is one of the time-consuming tasks encountered by forensic institutes. This paper proposes an effective scheme to match feature points and rotate the orientation of each fragment for banknote assembly. The experimental results...
The perception-based approach of feature extraction methods for CBIR has been summarized. It has proposed an experimental analysis of mathematical modeling of textural contents for images, having a perceptual meaning and application such as coarseness, directionality, contrast, and busyness. An objective is to find an effective method to estimate perceptual features. So a cumulative use of computational...
Initially appearing as an abstract object frequently used in math and physics, tensors have been attracting increasing interest in a broad range of research fields, such as engineering and data science. However, a few studies have addressed their application in wireless scenarios. In this paper, we investigate the wide applications of tensor techniques with an emphasis on the tensor voting method,...
Visual attention is one of the most important mechanisms in the human visual perception. Recently, its modeling becomes a principal requirement for the optimization of the image processing systems. Numerous algorithms have already been designed for 2D saliency prediction. However, only few works can be found for 3D content. In this study, we propose a saliency model for stereoscopic 3D video. This...
Micro blogging is fast becoming a dominant medium in social media and its impact is evident in our daily lives. A massive amount of information is produced on a daily basis. It is observed that detecting hot topics can be very helpful for people to get essential information quickly. But due to short and sparse features, high flood of meaningless tweets and other characteristics of micro blogs, traditional...
Sentiment Analysis is the process of determining subjectivity, polarity and polarity strength of a piece of text. Survey shows that 81% of Internet users have done on-line research on a product at least once. Manual analysis of this reviews is difficult. To mine the overall sentiment or opinion polarity, sentiment analysis can be used to mine the overall sentiment or opinion polarity of the review...
Playing a vital role, saliency has been widely applied for various image analysis tasks, such as content-aware image retargeting, image retrieval and object detection. It is generally accepted that saliency detection can benefit from the integration of multiple visual features. However, most of the existing literatures fuse multiple features at saliency map level without considering cross-feature...
Bag-of-Features (BOF) representation is a very popular model for content based image classification. In BOF, term frequency (tf) and inverse document frequency (idf) is a very popular model to compute the weights of the visual vocabularies. However, tf-idf model does not contain the class information of images. Fortunately, chi-square model contains the class information well. So, in order to enhance...
In this research a novel discriminative reordering model for statistical machine translation is proposed. Source dependency tree is used to define the orientation classes of the reordering model. We use maximum entropy principle to train the model. In addition to the common features used in the discriminative reordering models, two new and effective features are introduced. They are phrase number...
We investigate how overhead imagery can be integrated with non-image geographic data to learn appearance models for geographic objects with minimal user supervision. While multi-modal data integration has been successfully applied in other domains, such as multimedia analysis, significant opportunity remains for similar treatment of geographic data due to location being a simple yet powerful key for...
An information theoretic approach is proposed to estimate the degree of connectivity for each voxel with its neighboring voxels. The neighborhood system is defined by spatial and functional connectivity metrics. Then, a local mesh of variable size is formed around each voxel using spatial or functional neighborhood. The mesh arc weights, called Mesh Arc Descriptors (MAD), are estimated by a linear...
Visual saliency detection has become a challenging area in computer vision. In this paper, we propose a novel region based saliency detection model which considers background priors. The proposed method consists of two successive steps — region weighting and contrast computing. In the step of region weighting, we calculate the region weight for each region by region-level image feature and a log-linear...
This work describes the computation of scatterers that lay on the body of a real target which are depicted in radar images. A novelty of the approach is the target echoes collected by the radar are formulated into the first Fornasini-Marchesini (F-M) state space model [1] to compute poles that give rise to the scatterer locations in the two-dimensional (2-D) space. Singular value decomposition carried...
Visualization model of the coronary vasculature is of utmost importance for the diagnosis of the coronary heart diseases, as well as the planning and navigation of the intravascular surgery. To protect the cardiologists and operation staff against the ionizing radiation, surgical robots are designed and come to assist the practitioners during the interventional procedure. Robotic surgical simulation...
With the rapid development of microblog, the research of topic detection has been paid more attention, which has begun to transfer from the traditional news media to microblog. However, compared with the traditional fields where topic detection applied, the microblogging data is written informally and the structure of that is not rigorous, which will bring great difficulties. In the process of topic...
In this paper we present a method for the detection of wrong feature correspondences in a local feature based object detection system. Common visual objects in different images share not only similar local features but also a similar spatial layout of their features. We will utilize this fact in order to distinguish between correct and wrong feature correspondences. The spatial feature layout will...
In the context of a magnetic field-based indoor location system, this paper proposes a feature extraction process that uses magnetic-field temporal and spectral features in order to develop a classification model of indoor places, using only a magnetometer included in popular smartphones. We initially propose 46 features, 26 derived from the spectral evolution and 20 from the temporal one, chosen...
To enhance the understanding of human perception and mimic it into an artificial system, several types of graphical models have been proposed that emulate the functionality of neurons in biological neural networks. In this work, we investigate the discriminatory power of two such probabilistic models of vision: a multivariate Gaussian model [1] and a restricted Boltzmann machine [2], both widely used...
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