Shimin Feng

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In this paper we present a new method combining Mean Shift with Kalman filter for human tracking. Firstly, we use the Mean Shift algorithm based on color and texture features to calculate an accurate location in current frame. We select the HSV color space for calculating the histogram. Then Kalman filter is applied to predict the next initial searching(More)
In encumbered (e.g. carrying shopping bags) and walking situations, interacting with mobile phones is physically demanding and leads to poor input performance. This paper presents two user studies which investigate the effectiveness of using pressure as an alternative input modality to touch when using mobile phones while walking and encumbered.(More)
This thesis presents a new approach to multi-rate sensor fusion for (1) user matching and (2) position stabilisation and lag reduction. The Microsoft Kinect sensor and the inertial sensors in a mobile device are fused with a Gaussian Process (GP) prior method. We present a Gaussian Process prior model-based framework for multisensor data fusion and explore(More)
In this paper we present a novel Gaussian Process (GP) prior model-based sensor fusion approach to dealing with position uncertainty and lag in a system composed of an external position sensing device (Kinect) and inertial sensors embedded in a mobile device for user performance improvement. To test the approach, we conducted two experiments: (1) GPs sensor(More)
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