Word Recognition using Embedded Prototype Subspace Classifiers on a New Imbalanced Dataset

This paper presents an approach towards word recognition based on embedded prototype subspace classification.The purpose of this paper is three-fold. Firstly, a new dataset for word recognition is presented, which is extractedfrom the Esposalles database consisting of the Barcelona cathedral marriage records. Secondly, different clusteringtechniques are evaluated for Embedded Prototype Subspace Classifiers. The dataset, containing 30 different classesof words is heavily imbalanced, and some word classes are very similar, which renders the classification task ratherchallenging. For ease of use, no stratified sampling is done in advance, and the impact of different data splits isevaluated for different clustering techniques. It will be demonstrated that the original clustering technique based onscaling the bandwidth has to be adjusted for this new dataset. Thirdly, an algorithm is therefore proposed that findskclusters, striving to obtain a certain amount of feature points in each cluster, rather than finding some clustersbased on scaling the Silverman’s rule of thumb. Furthermore, Self Organising Maps are also evaluated as both aclustering and embedding technique.

Drone interactions within the field of Augmented Reality

Using drones and augmented reality paradigm, new forms of interactive algorithms has been created and proposed.We start with a first person view interaction where the drone mimics the movement of one person’s head wearing aHMD so that movements of the head can be mapped to actions by the drones. We then provide two novel AR/VRapplications of drones to create something similar to third person view in 2D and 3D. To get started, our firstidea is to control a drone using head movements. The second application which we implemented is to provide animplementation where tangible platforms are used by the drone to react to the movements of the character. Finallyour third implementaton if to create and AR world using real outdoor scenery and asking a drone to mimic a thirdperson view combining the real scenery with a synthetic actor so that based on the synthetic actor movement thedrone changes its behavior correctly in the real-word trying to provide a synchronized view of the real and syntheticword. There are three novel ideas providing a new form of interactions which will improve with drones functionalityin future. Our implementation shows the feasibility of our idea as discussed in the paper.

Interactive Individualized Neuroanatomy Labeling for Neuroanatomy Teaching

As the imaging technology and the understanding of neurological disease improve, a solid understanding of neu-roanatomy has become increasingly relevant. Neuroanatomy teaching includes the practice of cadaveric dissectionand neuroanatomy atlases consisting of images of a brain with its labeled structures. However, the natural inter-individual neuroanatomical variability cannot be taken into account. This work addresses the individual grossneuroanatomy atlas that could enrich medical students’ experiences with various individual variations in anatomi-cal landmarks and their spatial relationships. We propose to deform the CerebrA cortical atlas into the individualanatomical magnetic resonance imaging data to increase students’ opportunity to contact normal neuroanatomicalvariations in the early stages of studies. Besides, we include interactive queries on the labels/names of neu-roanatomical structures from an individual neuroanatomical atlas in a 3D space. An implementation on top ofSimpleITK library and VMTK-Neuro software is presented. We generated a series of surface and internal neu-roanatomy maps from 16 test volumes to attest to the potential of the proposed technique in brain labeling. Forthe age group between 10 to 75, there is evidence that the superficial cortical labeling is accurate with the visualassessment of the degree of concordance between the neuroanatomical and label boundaries.

New Methods and Novel Framework for HypersurfaceCurvature Determination and Analysis

New methods for hypersurface (that is, 3-dimensional manifold) curvature determination in volumetric data areintroduced. One method is convolution-based. Another method is spline-based. Method accuracy is also analyzed,with that analysis involving comparison of the methods with each other as well as against two existing convolution-based methods. The accuracy analysis utilizes a novel framework that enables curvature determination methodaccuracy analysis via dynamically generated synthetic test datasets formed from continuous trivariate functions.Such functions enable accuracy analysis versus ground truth. The framework is also described here.

FastRIFE: Optimization of Real-Time Intermediate Flow Estimation for Video Frame Interpolation

The problem of video inter-frame interpolation is an essential task in the field of image processing. Correctlyincreasing the number of frames in the recording while maintaining smooth movement allows to improve thequality of played video sequence, enables more effective compression and creating a slow-motion recording. Thispaper proposes the FastRIFE algorithm, which is some speed improvement of the RIFE (Real-Time IntermediateFlow Estimation) model. The novel method was examined and compared with other recently published algorithms.All source codes are available at:https://gitlab.com/malwinq/interpolation-of-images-for-slow-motion-videos.