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The main purpose of this paper is to develop a system for the early diagnosis and detection of abnormalities of any patient during gait cycle. A malfunction in the gait cycle leads to pain, and undesirable effects on the bones of the legs due to large forces exerted on specific areas. The gait cycle is divided into two main phases, the stance that is characterized as the contact of the right leg with...
Clinical chemistry tests are widely used in medical diagnosis. Physicians typically interpret them in a univariate sense, by comparing each parameter to a reference interval, however, their correlation structure may also be interesting, as it can shed light on common physiologic or pathological mechanisms. The correlation analysis of such parameters is hindered by two problems: the relationships between...
Missing data cases are a problem in all types of statistical analyses and arise in almost all application domains. Several schemes have been studied in this paper to overcome the drawbacks produced by missing values in data mining tasks, one of the most well known is based on pre processing, formerly known as imputation. In this work, we propose a new multiple imputation approach based on sampling...
This paper investigates the problem of cross-modal retrieval, where users can search results across various modalities by submitting any modality of query. Since the query and its retrieved results can be of different modalities, how to measure the content similarity between different modalities of data remains a challenge. To address this problem, we propose a joint graph regularized multi-modal...
Investigating potential dependencies in data and their effect on future business developments can help experts to prevent misestimations of risks and chances. This makes correlation a highly important factor in risk analysis tasks. Previous research on correlation in uncertain data management addressed foremost the handling of dependencies between discrete rather than continuous distributions. Also,...
In this paper we introduce an ant-based algorithm on continuous domains used to create procedural animations. We focus our approach on finding movement sequences that satisfy both the physical constraints as well as animator requirements. The proposed method is very flexible and can be easily adapted to different situations and characters' morphologies. Our simulations show that the proposed technique...
The knowledge of the segment parameters (SP) of the human body is crucial to understand, analyze and simulate human motions. The most recent technologies have enabled to identify the segment parameters, to compute in real-time variations of the Total Center of Mass (TCoM), or the Center of Pressure (CoP). These methods make use of costly and precise equipments, not easily portable for in-house personal...
The recent proliferation of graph data in a wide spectrum of applications has led to an increasing demand for advanced data analysis techniques. In view of this, many graph mining techniques, such as frequent subgraph mining and correlated subgraph mining, have been proposed. In many applications, both frequency and correlation play an important role. Thus, this paper studies a new problem of mining...
We study the retrieval of coloured textures from a database. In a statistical framework we model the heavy-tailed wavelet histograms through a generalized Gaussian distribution (GGD). We choose the Kullback-Leibler divergence (KLD) as a similarity measure and we obtain a closed-form expression for the KLD between two zero-mean bivariate GGDs. This allows us to take into account the rich correlation...
Sources of information in a multibiometric system are often assumed to be statistically independent in order to simplify the design of the fusion algorithm. However, the independence assumption may not be always valid. In this paper, we analyze whether modeling the dependence between match scores in a multibiometric system has any effect on the fusion performance. Our analysis is based on the likelihood...
In this paper, we propose a new method using joint features extracted from four efficient face illumination normalization approaches to deal with the face recognition problems under variable lighting conditions. These four methods (Logarithm Total Variation, Generic Intrinsic Illumination Subspace, Self-Quotient Image and Discrete Cosine Transform in Logarithm Domain) can indeed improve recognition...
This paper addresses the problem of defining a similarity measure between an observed Gaussian image and a binary image constructed from a cartographic database. The main idea is to assume that the binary image has been obtained by thresholding an unobserved Gaussian image correlated with the observed image. The proposed statistical model is then used to estimate its unknown parameters using the maximum...
Contact-free estimation of the human somatosensory information is an essential skill for robots working in daily environments. The main objective of this paper is to develop a method for estimating muscle tensions without any sensors attached to the body. Muscle tension is an important information for evaluating physical load during motions. Existing approaches utilizing optimization techniques and/or...
This research introduces an automatic scoring mechanism based on motion analysis of a player by video image processing and database of skills in gymnastics. The automatic scoring system will be made for the horizontal bar which is one of the gymnastics in particular. A scoring result is equivalent to scoring until now according to experience of a referee and the rulebook, or in order to perform highly...
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