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Automatic video keyword generation is one of the key ingredients in reducing the burden of security officers in analyzing surveillance videos. Keywords or attributes are generally chosen manually based on expert knowledge of surveillance. Most existing works primarily aim at either supervised learning approaches relying on extensive manual labelling or hierarchical probabilistic models that assume...
Background subtraction is a fundamental low-level processing task in numerous computer vision applications. The vast majority of algorithms process images on a pixel-by-pixel basis, where an independent decision is made for each pixel. A general limitation of such processing is that rich contextual information is not taken into account. We propose a block-based method capable of dealing with noise,...
We propose a quick and widely applicable approach for converting biometric identification match scores to probabilistic confidence scores, resulting in increased discrimination accuracy. This approach builds on a confidence scoring approach for Binomial distributions resulting from Hamming distances (commonly used in iris recognition). We derive a Gaussian confidence scoring approach that is three...
In recent years, there has been a growing interest in IP-reuse for SoCs in order to bridge the gap between the silicon capacity and the design productivity. This research work investigates how our proposed methodology can be used to partition and schedule a JPEG encoder IP core onto an FPGA. We will also describe a novel Constraint Satisfaction Problem (CSP) formulations that are used in the proposed...
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