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  <title><![CDATA[Ph.D. Proposal Oral Exam - Joshua Wells]]></title>
  <body><![CDATA[<p><strong>Title:&nbsp; </strong><em>Content-adaptive Cross-layer Optimized Video Processing using Real-time Feature Feedback</em></p><p><strong>Committee:&nbsp; </strong></p><p>Dr. Chatterjee, Advisor&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</p><p>Dr. Romberg, Chair</p><p>Dr. Raychowdhury</p><p><strong>Abstract:</strong></p><p>The objective of the proposed research is to design a low-power video processing system capable of minimizing power consumption through graceful reduction of the quality of the processed signal.&nbsp; Methods for post-processing signal analysis are proposed for determining the presence and quality of features essential to the high-level application goals.&nbsp; Two applications, video encoding and object tracking, are selected for study based on their high demand on mobile platforms.&nbsp; Methods for scaling the complexity of the entire system are proposed by simultaneously scaling down the input signal and algorithms to focus computational effort on information salient to the application.&nbsp; Dynamic voltage and frequency scaling (DVFS) is proposed along side error detection techniques.&nbsp; The voltage and frequency are to be scaled as low as possible (beyond design thresholds) without violating constraints on the quality of the application-specific measured features.&nbsp; Finally, a cross-layer control system is proposed for determining the optimal complexity scaling and DVFS.&nbsp; The control system will be charged with adjusting scaling levels to minimize power consumption while narrowly achieving the high-level application goals.&nbsp;</p>]]></body>
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