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The rising demand for energy growth worldwide is a major crisis in the present. Development of the renewable energy creates new efficient solutions to existing applications. Currently, solar power is the best renewable energy source. Air-conditioning provides comfort living in sub-tropical countries like Sri Lanka. Solar-powered air-conditioning will reduce the operating costs. Therefore, this paper focuses on design and construction of a solar-powered air-conditioner for automobiles. Implementation of the solar powered air-conditioner in an automobile, will increase the fuel efficiency while reducing the carbon emissions. Further, by isolating the compressor from the engine and powering through the solar energy, engine load decreases. Experimental calculations are presented considering a 35 seater bus.

A novel iris segmentation technique based on active contour is proposed in this paper. Our approach uses innovative algorithms, including two important ones, pupil segmentation and iris circle calculation. With our algorithms, we are able to find the center position and radius of pupil correctly and segment the iris precisely. The accuracy of our proposed method for ICE dataset is around 92% and also reached high accuracy level of 79% for UBIRIS. Our results demonstrate that the proposed iris segmentation method can perform well with high accuracy and better efficacy for Iris segmentation in images. Through a relatively high-performance algorithm to further cut up the round out the picture of the pupil conversion cutting growth square picture in order to make the judgment for biometric applications.

In this research, we propose a state-of-the-art 3D finger gesture tracking and recognition method. We use the depth sensors for both hands in real time music playing. In line with the development of 3D depth cameras, we implemented a set of 3D gesture-based instruments, such as Virtual Cello and Virtual Piano, which need precise finger tracking in 3D space. For hands tracking, model-based tracking for left hand and appearance-based tracking for right hand techniques are proposed. To detect finger gestures, our approaches consist number of systematic steps as reducing noise in depth map and geometrical processing for Virtual Cello. For Virtual Piano, we introduce the Neural Network (NN) method to detect special hand gestures. It has Multilayer Perceptron (MLP) structure with back propagation training. Literature has few examples using touch screen as medium, with fixed-coordinates, and 2D–gestures to control MIDI input. The end users should no longer carry anything on their hands. We use Senz3D and Leap Motion due to a few technical benefits. Senz3D and Leap Motion use a closer distance to hands, thus detailed finger gestures can be precisely identified. In the past years, we announced a set of virtual musical instruments and the MINE Virtual Band. Our research work is tested on lab environment and professional theatrical stage. More information and demonstrations of the proposed method can be accessed at: http://video.minelab.tw/DETS/VMIB/ .

Human Computer Interaction based Research has emerged in the early 1980s with the advent of computer technology. Human Motion Capture is the process of recording the movement of people. Among many kinds of human motion capture devises, Microsoft Kinect sensor and inertial sensors are most popular nowadays. In this paper we propose an efficient motion tracking mechanism to construct real time human skeleton animation using inertial sensors. We compare the results of our proposed method with the Microsoft Kinect sensor over the complicated motion tracking and joint position. During the experiment we observed that our results are much steady than Microsoft Kinect results. Some motions like hand cross over or leg cross over, our method showed better results than Kinect because the Kinect may lose skeleton of the blocked parts. On the other hand, since we use radio frequency inertial sensors, our method has a larger working area than Kinect.

3D model construction techniques using RGB-D information have been gaining a great attention of the researchers around the world in recent decades. The RGB-D sensor, Microsoft Kinect is widely used in many research fields, such as in computer vision, computer graphics, and human computer interaction, due to its capacity of providing color and depth information. This paper presents our research finding on calibrating information from several Kinects in order to construct a 3D model of a human object and to render texture captured from RGB camera. We used multiple Kinect sensors, which are interconnected in a network. High bit rate streams captured at each Kinect are first sent to a centralized PC for the processing. This even can be extended to a remote PC in the Internet. Main contributions of this work include calibration of the multiple Kinects, properly aligning point clouds generated from multiple Kinects, and generation of the 3D shape of the human objects. Experimental results demonstrate that the proposed method provides a better 3D model of the human object being captured.

Ubiquitous geometry (UG) system that was designed and developed for the sixth-grade school students to learn geometry through measuring geometric objects surrounding them is presented. Real geometric objects could facilitate and consolidate students' geometric learning if students were given an opportunity to apply and practice geometric concept-related theories with their daily life objects. Therefore, the main purpose of this study was an attempt to improve students' interest and learning in geometry by providing the proposed UG system in tablet computers to measure daily life objects. Furthermore, two activities, namely, peer assessment and competition, were also designed to facilitate students' interaction and learning. Based on the results of one of the experiments, it is found that students' learning motivation and achievement have been improved significantly. Further, results of the pair t-test applied for pretest and posttest data show that students' geometry learning performances have been improved significantly by using the UG system. Regarding the involvement of students in the proposed activities, it was found that the amounts of competition records, reviewing own competition records, and the highest score of competition were significantly correlated with students' learning gains. The reasons behind were further investigated and found that it can help students to find their own mistakes and clarify misconceptions by doing and reviewing their own competition records. Therefore, it is clear that the proposed UG system and competition activities in this study can help the students to learn geometry better in comparison to traditional learning.

With the advancements of the human computer interaction field, nowadays it is possible for the users to use their body motions, such as swiping, pushing and moving, to interact with the content of computers or smart phones without traditional input devices like mouse and keyboard. With the introduction of gesture-based interface Kinect from Microsoft it creates promising opportunities for educators to offer students easier and intuitive ways to interact with the learning systems. The integration of Kinect based applications into classroom make students' learning experience very active and joyful. In this context, this paper proposes a system for assessment in a smart classroom environment. An interactive framework is designed using Microsoft Kinect sensor for virtual learning environment with new gesture-based questions supporting QTI-based assessment, and further a rich set of gesture commands are also introduced for practical usage in the classroom. Proposed system was experimented with teachers and students then collected feedback of the users using a usability questionnaire. The results show that the participants are satisfied with the system and it demonstrates that the proposed system is simple to use, provides better functionality and motivates student learning by assessment.

An object surface extraction from a set of point clouds extracted using a Kinect V2 sensor is presented here. First several point clouds are extracted from different angles around the object. Second point clouds are registered with each other using the Iterative Closest Point algorithm. If the angle between two camera positions is large, point clouds are manually rough aligned. Then iterative closest point algorithm provides a finer alignment. Next the object boundary is found enclosing all the points in the aligned and merged point cloud. After that a triangular mesh is created with the boundary points. Finally colors acquired from the original point cloud are applied on the triangular surface generated. For a better visual effect colors of the points are interpolated on the triangular mesh generated.

In this paper we propose a novel method to improve seam carving based on the method meta-heuristic algorithms combining simulated annealing (SA) and genetic algorithm (GA). SA is a single solution method which searches locally while GA belongs to population based algorithms that globally search to find the best answer. By this strategy, both speed and quality of the seam carving method can be increased simultaneously. First, SA is performed to find near optimum seams, which form initial population of GA. Then genetic algorithm develops this initial population to find optimum seam. Experimental results show that search for optimum seams by our proposed method successfully improves the retargeting results of seam carving.

Usually in busy life styles as we experience today the time management has become a critical challenge. The extensive use of the technology made it easier to keep-up with the dynamical nature of life styles and accomplish daily requirements. When it comes to transportation, personal transportation has become a more popular. The main issue when we use our own transportation is the limitation of parking areas and there availability even though we find plenty of parking stations available. It is customary in peak hours the call centers in car parks are really busy and reserving parking slots has become impractical. This paper discusses not only the idea of implementing a GSM/GPRS framework to function an autonomous FIFO (First In First Out) based real time reservation mechanism for the dynamic vehicle parking environments but also has implemented a prototype of it and studied the adaptability of the algorithm in the prototype.

This paper presents authors experience about a completely online B. Sc. Degree program conducted in Sri Lanka at Rajarata University of Sri Lanka (RUSL). This degree program is offered in two main streams as Physical sciences and Bio sciences. Both degrees are three years in duration. Focus for this paper is two modules offered in the second year as a common module for both streams. Modules were conducted during February to May in 2013. Since the complete online nature of the program most of the students joined are employed. Moodle server is used to host all the course materials and assignments. Regular online discussion were carried out in order to answer students questions and to clarify unclear points. Students joined the discussion online from their homes mostly from all over the country. Twelve students were followed these modules and students who did not sit for the final exams were excluded from the statistical calculations.

Automatic text extraction from number plates is used in most of the countries in present. In this paper a semiautomatic text extraction from Sri Lankan vehicle number plates is presented. There are several number plate types currently available in Sri Lanka. First a set of template was created based on the font used in the number plates for all the English letters and numbers. Number plate first corrected as can be seen from a camera situated in front of the camera. Then the area of the numbers is extracted. Texts and numbers are then separated in to separate images. Finally separated texts and numbers are matched with the original template created using template matching. A data set consisted of 93 number plates is used to demonstrate the usability of the proposed method.

Panorama photos are very useful when capturing large scenic backgrounds like famous constructions or eye catching landscapes. Users normally prefer capturing such backgrounds with them or friends as the foreground, but the moving people in such popular locations always obstruct the iconic structure in the background. In this paper a solution for automatic panorama generation is presented which is capable of removing moving objects in the background. First user captures a short video starting from the centre of the focus area and then following a clockwise circular path. The proposed application generates the panorama based on input video following the steps: segmentation of human object, removal of moving human objects, and generation of panorama. Experimental output panorama photos show that the proposed system is very usable and results are satisfactory.

Human Computer Interaction is becoming a major component in computer science related fields allowing humans to communicate with machines in very simple ways exploring new dimensions of research. Kinect, the 3D sensing device introduced by Microsoft mainly aiming computer games domain now is used in different scopes, one is being generation or controlling of sound signals producing aesthetic music. Here, in this paper, authors' experimental efforts on three virtual music instruments: Drum, Guitar and Spider King, based on Kinect sensor are presented. All three instruments virtually set the relevant sensing input areas, as an example, strings of the guitar or cymbals of the drum, then, the player controls the instrument through those virtual inputs through the Kinect. Sound control data is then generated and fed to the audio library based on the musically oriented human computer interaction gestures, composing a realtime musical expressive performance. A live performance using the presented virtual instruments was carried out at the end.