This paper presents a model for communication between mobile devices and TV programs, through applications that use a middleware named Ginga, proposing a generic architecture that allows a single mobile application interact with various Ginga applications. A fundamental requirement for the project is the definition of a model that allows iDTV (interactive Digital Television) applications communicate with devices of various operating systems. Despite the increasing and fast use of various portable devices around the world, including Brazil, simultaneously the traditional way of watching television, there is still a lack of direct interaction between TV programming and the second screen of the viewer. The proposed model consists of an application for the Android mobile operating system and other developed NCLua ginga connected by a wireless network, enabling communication, control and interaction via smartphone. The components of the model, its main features, results and difficulties in the construction of the platform are presented.

In this work, we propose a workflow for face recognition under occlusion using the entropy projection from the curved Gabor filter, and create a representative and compact features vector that describes a face. Despite the reduced vector obtained by the entropy projection, it still presents opportunity for further dimensionality reduction. Therefore, we use a Random Forest classifier as an attribute selector, providing a 97% reduction of the original vector while keeping suitable accuracy. A set of experiments using three public image databases: AR Face, Extended Yale B with occlusion and FERET illustrates the proposed methodology, evaluated using the SVM classifier. The results obtained in the experiments show promising results when compared to the available approaches in the literature, obtaining 98.05% accuracy for the complete AR Face, 97.26% for FERET and 81.66% with Yale with 50% occlusion.

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