In this paper we present hand and foot based immersive multimodal interaction approach for handheld devices. A smart phone based immersive football game is designed as a proof of concept. Our proposed method combines input modalities (i.e. hand & foot) and provides a coordinated output to both modalities along with audio and video. In this work, human foot gesture is detected and tracked using template matching method and Tracking-Learning-Detection (TLD) framework. We evaluated our system's usability through a user study in which we asked participants to evaluate proposed interaction method. Our preliminary evaluation demonstrates the efficiency and ease of use of proposed multimodal interaction approach.

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In this paper we propose a simple and novel method for head pose estimation using 3D geometric modeling. Our algorithm initially employs Haar-like features to detect face and facial features area (more precisely eyes). For robust tracking of these regions; it also uses Tracking-Learning-Detection(TLD) frame work in a given video sequence. Based on two human eye-areas, we model a pivot point using distance measure devised by anthropometric statistic and MPEG-4 coding scheme. This simple geometrical approach relies on human facial feature structure on the camera-view plane to estimate yaw, pitch and roll of the human head. The accuracy and effectiveness of our proposed method is reported on live video sequence considering head mounted inertial measurement unit (IMU).

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