Time Complexity of Color Camera Depth Map Hand Edge Closing Recognition Algorithm

The objective of this paper is to calculate the time complexity of the colored camera depth map hand edge closing algorithm of the hand gesture recognition technique. It has been identified as hand gesture recognition through human-computer interaction using color camera and depth map technique, which is used to find the time complexity of the algorithms using 2D minima methods, brute force, and plane sweep. Human-computer interaction is a very much essential component of most people's daily life. The goal of gesture recognition research is to establish a system that can classify specific human gestures and can make its use to convey information for the device control. These methods have different input types and different classifiers and techniques to identify hand gestures. This paper includes the algorithm of one of the hand gesture recognition “Color camera depth map hand edge recognition” algorithm and its time complexity and simulation on MATLAB

Outdoor 3D illumination in real time environments: A novel approach

Comprehensive enlightenment is one of the fundamental components that virtualize the real environment. Accordingly, sky shading is one of the important components considered in the virtualization process. This research introduces the Dobashi method of sky luminance; additionally, Radiosity Caster Culling is applied to the virtual objects as the second thought for outside illumination. Pre-Computed Radiance Transfer is connected to ascertain the division of patches. Moreover, for real sky shading, the Perez model is utilized. By pre-ascertaining sky shading vitality and outside light, the vitality of the entire open air is figured ahead of time. The open air vitality is shared on virtual articles to make the situations more practical. Commercial videos and cartoon creators could utilize the strategy to produce real outside situations. © 2017

New generation of human machine interfaces for controlling UAV through depth based gesture recognition

New forms of natural interactions between human operators and UAVs (Unmanned Aerial Vehicle) are demanded by the military industry to achieve a better balance of the UAV control and the burden of the human operator. In this work, a human machine interface (HMI) based on a novel gesture recognition system using depth imagery is proposed for the control of UAVs. Hand gesture recognition based on depth imagery is a promising approach for HMIs because it is more intuitive, natural, and non-intrusive than other alternatives using complex controllers. The proposed system is based on a Support Vector Machine (SVM) classifier that uses spatio-temporal depth descriptors as input features. The designed descriptor is based on a variation of the Local Binary Pattern (LBP) technique to efficiently work with depth video sequences. Other major consideration is the especial hand sign language used for the UAV control. A tradeoff between the use of natural hand signs and the minimization of the inter-sign interference has been established. Promising results have been achieved in a depth based database of hand gestures especially developed for the validation of the proposed system

GESTURE RECOGNITION FOR PENCAK SILAT TAPAK SUCI REAL-TIME ANIMATION

The main target in this research is a design of a virtual martial arts training system in real-time and as a tool in learning martial arts independently using genetic algorithm methods and dynamic time warping. In this paper, it is still in the initial stages, which is focused on taking data sets of martial arts warriors using 3D animation and the Kinect sensor cameras, there are 2 warriors x 8 moves x 596 cases/gesture = 9,536 cases. Gesture Recognition Studies are usually distinguished: body gesture and hand and arm gesture, head and face gesture, and, all three can be studied simultaneously in martial arts pencak silat, using martial arts stance detection with scoring methods. Silat movement data is recorded in the form of oni files using the OpenNI ™ (OFW) framework and BVH (Bio Vision Hierarchical) files as well as plug-in support software on Mocap devices. Responsiveness is a measure of time responding to interruptions, and is critical because the system must be able to meet the demand

A novel approach of multimedia instruction applications in engineering education

Effective use of educational technology depends on knowledge of why and how to utilize technology to solve teaching and learning problems. The present study first conducts a systematic literature review of the limited studies undertaken on multimedia instruction applications for engineering education to critique the current status of knowledge in this area. The conventional qualitative content analysis method was employed for data analysis. The results highlighted the incompatibility of three basic educational elements i.e. engineering curriculum, educational resources and engineering students’ learning characteristics all of which posed major challenges in teaching and learning engineering courses. Multimedia instruction enhances engineering students’ understanding of engineering concepts, procedures, problems and solutions through direct visualization. Furthermore, it could indirectly assist students in achieving higher order learning levels and skills through enhancing or supporting educational resources and increasing students’ motivation. Mobile multimedia instruction and a student-generated multimedia learning approach to improve engineering education are suggested for future research