Binary morphological shape-based interpolation applied to 3-D tooth reconstruction

In this paper we propose an interpolation algorithm using a mathematical morphology morphing approach. The aim of this algorithm is to reconstruct the $n$-dimensional object from a group of (n-1)-dimensional sets representing sections of that object. The morphing transformation modifies pairs of consecutive sets such that they approach in shape and size. The interpolated set is achieved when the two consecutive sets are made idempotent by the morphing transformation. We prove the convergence of the morphological morphing. The entire object is modeled by successively interpolating a certain number of intermediary sets between each two consecutive given sets. We apply the interpolation algorithm for 3-D tooth reconstruction

Prediction and Tracking of Moving Objects in Image Sequences

We employ a prediction model for moving object velocity and location estimation derived from Bayesian theory. The optical flow of a certain moving object depends on the history of its previous values. A joint optical flow estimation and moving object segmentation algorithm is used for the initialization of the tracking algorithm. The segmentation of the moving objects is determined by appropriately classifying the unlabeled and the occluding regions. Segmentation and optical flow tracking is used for predicting future frames

Multimodal decision-level fusion for person authentication

In this paper, the use of clustering algorithms for decision-level data fusion is proposed. Person authentication results coming from several modalities (e.g., still image, speech), are combined by using fuzzy k-means (FKM), fuzzy vector quantization (FVQ) algorithms, and median radial basis function (MRBF) network. The quality measure of the modalities data is used for fuzzification. Two modifications of the FKM and FVQ algorithms, based on a novel fuzzy vector distance definition, are proposed to handle the fuzzy data and utilize the quality measure. Simulations show that fuzzy clustering algorithms have better performance compared to the classical clustering algorithms and other known fusion algorithms. MRBF has better performance especially when two modalities are combined. Moreover, the use of the quality via the proposed modified algorithms increases the performance of the fusion system

Investigation of polymeric coatings by electrodeless discharge Final report

Polymeric films deposited by electrical discharge from hydrocarbon

Exploring the parent-coach and child-athlete relationship in the recreational sport context

Parent-coaches are individuals who coach their own children (child-athletes) in sports. Although their presence is widespread in the realm of recreational sports, little research has been conducted on the relationship between parent-coach and child-athlete. This is an exploratory study with the goal of better understanding the parent-coach phenomenon in the recreational sports context, from the perspective of both parent-coaches and child-athletes. Semi-structured interviews were conducted with nine parent-child dyads, focusing on positives, negatives, and the unique nature of the parent-coach and child-athlete relationship. Inductive analysis revealed a number of positive and negative themes, many of which were identified by both parent-coaches and child-athletes. Both parent-coaches and child-athletes perceived higher expectations for child-athletes, as well as a desire for equal treatment of all athletes on a team. Suggestions for applications to coaching education, as well as possible implications for future research are discussed