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The interest point (IP) matching algorithms match the points either locally or spatially. We propose a local-spatial IP matching algorithm usable for articulated human body tracking. The local-based stage finds matched IP pairs of two reference and target IP lists using a local-feature-descriptors-based matching method. Then, the spatial-based stage recovers more matched pairs from the remaining unmatched...
In this paper, we propose to combine the shape context (SC) descriptor with quantum genetic algorithms (QGA) to define a new shape matching and retrieval method. The SC matching method is based on finding the best correspondence between two point sets. The proposed method uses the QGA to find the best configuration of sample points in order to achieve the best possible matching between the two shapes...
This paper presents a proposal for the use of Spatial Augmented Reality as a tool for 3D data visualizations. The use of traditional display technologies such as LCD monitors provides a fish tank metaphor for the user, i.e. the information is behind a plane of glass. The use of VR technologies allows the user to be immersed in the 3D volume and remove this fish tank problem, but can limit the set...
The question whether to use 2D or 3D for data visualization is generally difficult to decide. Two-dimensional and three-dimensional visualization techniques exhibit different advantages and disadvantages related to various perceptual and technical aspects such as occlusion, clutter, distortion, or scalability. To facilitate problem understanding and comparison of existing visualization techniques...
This paper reports on the urban installation SoundscapesLandscapes (SSLS), an enhanced sound walk guided by a custom mobile application. It explores the aesthetic motivations of the artists involved before examining the manner in which these motivations shape the rationale and design of the project. Creative issues are approached from a musical perspective, and the focus of the paper is to place the...
Scene text recognition has attracted much attention in the research community. Many proposed scene text recognition methods adopt a step-by-step procedure, which includes a text extraction phase and a recognition phase. In this study, in order to eliminate the risk of text extraction error, we try to build a scene text recognition system that does not involve the text extraction phase. In our proposed...
This paper presents a study on the peculiarities of the plant augmentation by integrators in the discrete-time LQG/LTR control. In the LQG/LTR methodology, the inclusion of “free” integrators in each control channel of the plant helps the designer to define a Target Feedback Loop with good performance characteristics in the mixed-sensitivity analysis. However, due to specific conditions of the discrete-time...
In this paper, we present a conceptual design for a context-influenced Long-Term Memory architecture. The notion of context is used as a means to organize the information flow between the Working Memory and Long-Term Memory components. In particular, we discuss the major influence of the notion of context within the Episodic Memory on the Semantic and Procedural Memory, respectively. In other words,...
With the increasing needs from a variety of real world applications like context retrieval and aid reading, scene text recognition is attracting more and more attention from the computer vision community. Scene text character (STC) recognition plays an important role in this task. However, recognition of STC is a challenging task due to a series of problems, like different illumination conditions,...
Considering the requirement for a more objective result of image retrieval, the features of image itself attract more and more attentions of researchers. Recently, the shape context of images is widely applied in image matching for its good invariance of translation and scale, as well as its good robust for small geometric distortion. Thus, the features of shape context are introduced in this paper...
Silhouettes are frequently extracted and described to compose inputs for learning methods in solving human pose estimation problem. Although silhouettes extracted from background subtraction methods are usually noisy, the effect of noisy inputs to pose estimation accuracies is seldom studied. In this paper, we explore this problem. First, We compare performances of several image features widely used...
We present an approach for object class learning using a part-based shape categorization in RGB-augmented 3D point clouds captured from cluttered indoor scenes with a Kinect-like sensor. We propose an unsupervised hierarchical learning procedure which allows to symbolically classify shape parts by different specificity levels of detailedness of their surface-structural appearance. Further, a hierarchical...
This paper presents a new approach to multi-robot environment exploration based on label maps building through recognition of frontiers. At first, the model of multi-robot environment exploration is built and analysed, in which, the label map building, the formation and role modeling, and the task assignment are synthetically considered. Then the behavior coordination towards exploration process is...
In MANETs, communication often relies on finding a set of sequential opportunistic encounters between pairs of mobile nodes. In this context, understanding mobile node behaviour is essential to design effective and efficient network protocols. One characteristic that emerges from node mobility is that mobile nodes often have periodic behaviours. In this paper we take advantage of periodically repeated...
In the context of handwritten mathematical expressions recognition, a first step consist on grouping strokes (segmentation) to form symbol hypotheses: groups of strokes that might represent a symbol. Then, the symbol recognition step needs to cope with the identification of wrong segmented symbols (false hypotheses). However, previous works on symbol recognition consider only correctly segmented symbols...
This paper proposes the improvement of context dependent modeling for Arabic handwriting recognition. Since the number of parameters in context dependent models is huge, CART trees are used for state tying. This work is based on a new set of questions for the CART tree construction based on a "lossy mapping" categorization of the Arabic shapes. The used system is a combination of Hidden...
The location security in current location-based services (LBS) meets threat where mobile users have to report their actual location knowledge to the LBS provider in order to get their desired POI, (Points of Interests). We consider location privacy techniques that work using obfuscation operators and provide different information services using different cloaking techniques without any trusted components...
Touching components are connection zones occurring between text-lines or words of the same line and are one of the problems that make unconstrained handwritten text segmentation greatly hard. In this paper, we propose a recognition based method to separate these components once localized in Arabic manuscript images. It first identifies, for a given touching component, a similar model stored in a dictionary...
In this paper we evaluate the influence of the selection of key points and the associated features in the performance of word spotting processes. In general, features can be extracted from a number of characteristic points like corners, contours, skeletons, maxima, minima, crossings, etc. A number of descriptors exist in the literature using different interest point detectors. But the intrinsic variability...
We investigate the task of single-stroke classification into one of three classes (text, figure, or table rule lines). Individual strokes form handwriting structures such as text lines, figures, and tables in combination with peripheral strokes. To classify strokes using local contexts of neighborhood strokes, we propose a composite descriptor that represents in detail the relation between individual...
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