Automatic Article Detection in a Jumbled Scene Using Point Feature Matching

Recognition of items in jumbled scenes is a basic test that has as of late been generally embraced by computer vision frameworks. This chapter proposes a novel technique how to distinguish a specific item in jumbled scenes. Given a reference picture of the article, a method for recognizing a particular article dependent on finding point correspondences between the reference and the objective picture is presented. It can distinguish objects in spite of a scale change or in-plane revolution. It is additionally strong to little measure of out-of-plane rotation and occlusion. This technique for article location works for things that show non-reiterating surface precedents, which offer rising to exceptional part coordinates. This method furthermore works honorably for reliably shaded articles or for things containing repeating structures. Note that this calculation is intended for recognizing a particular article.

The Way-Finding in Educational Modular Buildings: The Case of the Male Engineering Building at Qatar University

Way-finding is the ability of people to perceive routes, flow patterns, or passageways inside and/or around a building. In other words, it is the capability of a person to know their whereabouts in a space. Modular buildings and complex spatial plan structure, in general, can be very confusing, especially from a way-finding point of view. This research attempts to measure the way-finding performance of a modular building by assessing the users’ experience in finding their way inside the Male Engineering Building at Qatar University. The study involved students, faculty, and staff members that utilize that space daily. The research focused on accessing indoor spaces as well as the walkways and spaces connected to the building. Results show that parameters as the use of colours and numbers can improve capability and swiftness in way-finding. In future research, several types of signage and visual elements will be tested, in order to understand how they can enhance way-finding efficiency and user performance within indoor spaces.

Homography estimation for low-contrast IR image sequences utilizing GPS control points

Estimating the homographies for IR sequences of approaching objects in the infrared spectrum is a special problem. Due to the approaching movement of a helicopter towards measurement items, the objects are represented with few pixels in the beginning of the sequence and they are represented with a lot more pixels when reaching the destination area. This fact results in an assignment problem of finding point correspondences. This difficulty has led to drifting phenomena when using sophisticated methods for estimating the homographies. In this article a method is described which eliminates both the problem of finding point correspondences as well as the drifting issue. The presented procedure exploits information gathered by additional sensors (i. e., a GPS receiver, an inertial measurement unit (IMU), and a compass) for the computation of camera projections for each frame. The camera mappings are used to project GPS control points into the frames. The use of the same GPS points for each frame results in naturally given point correspondences. Using these correspondences the homographies can be estimated. The results are compared to the state of the art.

Student Perceptions and Satisfaction with Online and Distance Learning

Online learning is more and more popular in colleges in recent years, but it still remains at a budding stage of its development. It needs more adjustment to meet the students requirements. So firstly, we should get more feedback or insight on how the students perceive and suggestions to online courses. By analyzing the problems with online learning, and basing on the literature review, this article gives the finding point and conclusion. And that is supposed to help both the instructors and the administrators decide if the school should continue their online learning programs.

Numerical Version of the Non-Uniform Method for Finding Point Estimates of Uncertain Scaling Constants

The chapter focuses on the analysis of scaling constants when constructing a utility function over multi-dimensional prizes. Due to fuzzy rationality, those constants are elicited in an interval form. It is assumed that the decision maker has provided additional information describing the uncertainty of the scaling constants’ values within their uncertainty interval. The non-uniform method is presented to find point estimates of the interval scaling constants and to test their unit sum. An analytical solution of the procedure to construct the distribution of the interval scaling constants is provided, along with its numerical realization. A numerical procedure to estimate pvalue of the statistical test is also presented. The method allows making an uncertainty description of constants through different types of probability distributions and fuzzy sets.