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A coarse integral holography approach for real 3D colour video display

A coarse integral holography approach for real 3D colour video display

by Martina Megaro | Mar 17, 2016 | Visual Computing, Visual Display Technology

A coarse integral holography approach for real 3D colour video display   We have developed a dynamic coarse integral holography approach using opto-mechanical scanning, coarse integral optics and a low space-bandwidth-product high-bandwidth spatial light modulator to...
Underwater 3D Capture using a Low-Cost Commercial Depth Camera

Underwater 3D Capture using a Low-Cost Commercial Depth Camera

by Martina Megaro | Mar 7, 2016 | Capture, Visual Computing

Underwater 3D Capture using a Low-Cost Commercial Depth Camera   This paper presents underwater 3D capture using a commercial depth camera. March 7, 2016IEEE Winter Conference on Applications of Computer Vision (WACV) 2016   Authors Sundara Tejaswi Digumarti...
Experimental Characterization of 802.11ac Indoor Performance and Fairness

Experimental Characterization of 802.11ac Indoor Performance and Fairness

by Martina Megaro | Mar 3, 2016 | Visual Computing, Wireless Communication and Ubiquitous Computing

Evaluating 802.11ac Features in Indoor WLAN- An Empirical Study of Performance and Fairness   We present a thorough and extensive experimental performance characterization of the achievable data throughput, jitter, and fairness of the IEEE 802.11ac standard for indoor...
Trending Paths: A Metric for Evaluating Crowd Simulation

Trending Paths: A Metric for Evaluating Crowd Simulation

by Martina Megaro | Feb 26, 2016 | Video Processing, Visual Computing

Trending Paths: A Metric for Evaluating Crowd Simulation   We propose a new approach based on finding latent Path Patterns in both real and simulated data in order to analyze and compare them. February 26, 2016ACM SIGGRAPH Symposium on Interactive 3D Graphics and...
Assumed Density Filtering Methods for Scalable Learning of Bayesian Neural Networks

Assumed Density Filtering Methods for Scalable Learning of Bayesian Neural Networks

by Martina Megaro | Feb 12, 2016 | Machine Learning

Assumed Density Filtering Methods for Scalable Learning of Bayesian Neural Networks   In this paper, we first rigorously compare the two algorithms and in the process develop several extensions, including a version of EBP for continuous regression problems and a PBP...
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