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Document Type : Latin Dissertation
Language of Document : English
Record Number : 149957
Doc. No : ET21749
Main Entry : Gang Hua
Title Proper : Probabilistic Variational Methods for Vision based Complex Motion Analysis
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : Many emerging applications, including intelligent vision based human computer interaction,intelligent video surveillance, virtual and augmented reality, animation, and biomedical imageanalysis for computer aided diagnosis and surgery, demand eective and ecient visionbasedmethods to analyze complex motions, such as articulated motion, deformable motion,and multiple motions. The fundamental challenges of this inverse problem come from twoaspects: the high degrees of freedom in these complex motions, and the complications in theimage measurements. The high dimensionality of this problem has plagued the scalabilityand eciency of many existing methods.In search for a new and scalable solution that overcomes the curse of dimensionality, weview this problem from another angle and conjecture that the complexity of such a problemcan be approached by the collaboration among a set of low dimensional motion estimators.Targeting on the two fundamental challenges, in this dissertation, we propose a distributedand collaborative probabilistic reasoning framework..tested for theQ1 PC1 bus cardBoth these projects mere sofixare des elopment efforts tonards contributing to dlfferentaspects of Roboucs and lZ1echatronics projects m the Controls and Roboucs Group..
Subject : Electericl tess
: برق
electronic file name : TL44931.pdf
Title and statement of responsibility and : Probabilistic Variational Methods for Vision based Complex Motion Analysis [Thesis]
 
 
 
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