Mobile Augmented Reality (MAR) is becoming an important cyber-physical

MobiCoStream, an acronym for Mobile Collaborative upStream, refers to Real-time video upstream of captured video in Mobile Augmented Reality (MAR) applications. MAR for tele-assistance deals with providing real-time assistance to the user through the power of Augmented Reality. Real-time applications have strict delay requirements which need to be met in order to satisfy the user Quality of Service (QoS). Mobile communication still being in its third generation, limits the availability of high up-link bandwidth for video transmission. The problem is tackled by means of Bandwidth Aggregation through which the hand-held devices in the vicinity, collaborate with the user to achieve real-time video up-link and maintain the user QoS. In this paper, we present the actual results pertaining to the prototype implementation of the proposed system. Also presented are some simulation results, by viewing the multiple hand-held devices as a virtual Multiple Input Multiple Output (MIMO) system and in turn considering the popular Alamouti scheme in this context.

Mobile Augmented Reality (MAR) is an emerging field and its nascent applications are finding its ways into the current deployments of cyber physical system. Mobile devices can harness augmented reality technology in any unprepared environment. This introduces a challenge to achieve an accurate and robust registration and tracking of mobile device. For accurate tracking, much research is being carried out to fuse inertial and vision sensor data. The resultant tracking can be further made better by finding means to track coupled translational and rotational motions. This problem is tackled with a neat formalism in terms of dual quaternion. Unit dual quaternion can capture the coupling between translational and rotational motions. In this paper, the requisite machinery is pivoted around Extended Kalman Filter (EKF) and is derived based on dual quaternion. The derived EKF expression is verified through experimentation involving both simulated and realistic data, the latter being obtained from a prototype for MAR. The simulation results show the effectiveness of dual quaternion on position and orientation estimation. This novel fusion framework resulted in more accurate tracking as compared to that of the existing quaternion based algorithm.

Contactless displacement measurement using low-cost sensor modules is vital in engineering applications like elevators. To achieve contactless displacement measurement with high resolution and reliability, a new method of Displacement Estimation on Navigators (DEON) is proposed. The purpose of the proposed approach is to estimate the navigator’s motion using a micro electro mechanical system based accelerometer and to compute the actual displacement covered by the navigators. The error profiles are analysed in acceleration signal which is captured by the accelerometer and it is extracted and calibrated to remove the offset drift error. Further, the data has been processed to reduce random drift error by applying the Savitzky–Golay filter. Then, the principles of integral calculus are applied in the time-domain and displacement is obtained by integrating acceleration twice. The proposed algorithm aimed at measuring displacement caused by the vibration to the object. The similarity between actual and estimated displacement is 98%.

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