This article proposes a real-time Head Pose Estimation (HPE) technique designed to be used in mobile devices. The method enables the interaction between the user and mobile devices using the device's inbuilt camera. The proposed technique is composed of different computer vision methods, which were optimized to operate in a restricted environment. The method has three Degrees of Freedom (DOF), roll, yaw and pitch. The HPE is obtained using these movements. Experiments were conducted using 363 videos of 27 different people taken in varied scenarios with changes in illumination and background. The results demonstrate the robustness and efficiency of the proposed method.

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Nowadays multi-core processors can be found everywhere. It is well known that one way of improving performance is by parallelization. In this paper we propose a parallelization strategy for Java using algebraic laws. We perform an experiment with two benchmarks and show that our strategy produces a gain similar to a specialized parallel version provided by the Java Grande Benchmark (JGB).