This paper proposed and verified a new integrated approach based on the iterative super-resolution algorithm and expectation-maximization for face hallucination, which is a process of converting a low-resolution face image to a high-resolution image. The current sparse representation for super resolving generic image patches is not suitable for global face images due to its lower accuracy and time-consumption. To solve this, in the new method, training global face sparse representation was used to reconstruct images with misalignment variations after the local geometric co-occurrence matrix. In the testing phase, we proposed a hybrid method, which is a combination of the sparse global representation and the local linear regression using the Expectation Maximization (EM) algorithm. Therefore, this work recovered the high-resolution image of a corresponding low-resolution image. Experimental validation suggested improvement of the overall accuracy of the proposed method with fast identification of high-resolution face images without misalignment.

Nowadays, almost all applications, especially augmented reality (AR) applications, run on the web. In these applications, determining the position and rotation of the mobile device is an indispensable basic step. The speed and accuracy of this work greatly affect the quality of the user experience. Therefore, estimating the rotational position of mobile devices on the Web is necessary and meaningful in practice. In this paper, we propose a way to estimate the position and rotation of the mobile device using the image of the marker obtained from the camera combined with the data from the device’s tilt angle sensor. The proposal has been experimentally installed and evaluated for performance onWeb Assembly, Java Script, and C++ platforms. Along with that, to ensure objectivity, we compared the speed and calculation error of the proposed technique with the P3P and PnP techniques installed in the OpenCV open-source library. We also use the proposal method to develop the Virtual Museum application for the Vietnam National Museum of Nature

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