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Showing result 1 - 5 of 8 swedish dissertations matching the above criteria.
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1. Stochastic Modeling for Video Object Tracking and Online Learning: manifolds and particle filters
Abstract : Classical visual object tracking techniques provide effective methods when parameters of the underlying process lie in a vector space. However, various parameter spaces commonly occurring in visual tracking violate this assumption. READ MORE
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2. Expressing emotions through vibration for perception and control
Abstract : This thesis addresses a challenging problem: “how to let the visually impaired ‘see’ others emotions”. We, human beings, are heavily dependent on facial expressions to express ourselves. A smile shows that the person you are talking to is pleased, amused, relieved etc. READ MORE
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3. Visual Object Tracking and Classification Using Multiple Sensor Measurements
Abstract : Multiple sensor measurement has gained in popularity for computer vision tasks such as visual object tracking and visual pattern classification. The main idea is that multiple sensors may provide rich and redundant information, due to wide spatial or frequency coverage of the scene, which is advantageous over single sensor measurement in learning object model/feature and inferring target state/attribute in complex scenarios. READ MORE
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4. Riemannian Manifold-Based Modeling and Classification Methods for Video Activities with Applications to Assisted Living and Smart Home
Abstract : This thesis mainly focuses on visual-information based daily activity classification, anomaly detection, and video tracking through using visual sensors. The main reasons for adopting visual-information based methods are due to: (i) vision plays a major role in recognition/classification of activities which is a fundamental issue in a human-centric system; (ii) visual sensor-based analysis may possibly offer high performance with minimum disturbance to individuals' daily lives. READ MORE
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5. Singular Value Computations for Toeplitz Matrices and Subspace Tracking
Abstract : This thesis addresses the problem of computing the largest singular values and corresponding singular vectors of a Toeplitz matrix. These are often requested in signal processing and system identification to extract the signal from the noise. READ MORE