GH
G.F.L. Hellouin de Ménibus
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The Three Flatland Problem
HUD content for Augmented Reality Multiplicative Light Field Displays
Master thesis
(2025)
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G.F.L. Hellouin de Ménibus, R. Guerra Marroquim, P. Kellnhofer, M.A. Zuñiga Zamalloa
One of AR's promising developments is the delivery of critical information at just the right time.
Light field displays (LFDs) stand out as a potential foundation for AR. Several AR applications use simple HUDs, primarily projecting 2D elements (e.i. outlines, text, glyphs) to deliver critical information. Despite this, most approaches still employ complex 3D rendering techniques to display the content.
Our approach, by contrast, leverages the content's 2D nature to achieve lower sampling times, more efficient memory representation and can be extended to support 2D animated content.
We build on top of work in light field displays, allowing us to maintain correct focus cues and stereoscopy.
More specifically, we report a 100-fold improvement in sampling times, and a minor improvement in rendering time. ...
Light field displays (LFDs) stand out as a potential foundation for AR. Several AR applications use simple HUDs, primarily projecting 2D elements (e.i. outlines, text, glyphs) to deliver critical information. Despite this, most approaches still employ complex 3D rendering techniques to display the content.
Our approach, by contrast, leverages the content's 2D nature to achieve lower sampling times, more efficient memory representation and can be extended to support 2D animated content.
We build on top of work in light field displays, allowing us to maintain correct focus cues and stereoscopy.
More specifically, we report a 100-fold improvement in sampling times, and a minor improvement in rendering time. ...
One of AR's promising developments is the delivery of critical information at just the right time.
Light field displays (LFDs) stand out as a potential foundation for AR. Several AR applications use simple HUDs, primarily projecting 2D elements (e.i. outlines, text, glyphs) to deliver critical information. Despite this, most approaches still employ complex 3D rendering techniques to display the content.
Our approach, by contrast, leverages the content's 2D nature to achieve lower sampling times, more efficient memory representation and can be extended to support 2D animated content.
We build on top of work in light field displays, allowing us to maintain correct focus cues and stereoscopy.
More specifically, we report a 100-fold improvement in sampling times, and a minor improvement in rendering time.
Light field displays (LFDs) stand out as a potential foundation for AR. Several AR applications use simple HUDs, primarily projecting 2D elements (e.i. outlines, text, glyphs) to deliver critical information. Despite this, most approaches still employ complex 3D rendering techniques to display the content.
Our approach, by contrast, leverages the content's 2D nature to achieve lower sampling times, more efficient memory representation and can be extended to support 2D animated content.
We build on top of work in light field displays, allowing us to maintain correct focus cues and stereoscopy.
More specifically, we report a 100-fold improvement in sampling times, and a minor improvement in rendering time.
Why Midas would be a terrible secretary
Using a greedy approach to enhance SAT for the Preemptive Resource-Constrained project scheduling problem with set up time
Bachelor thesis
(2023)
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G.F.L. Hellouin de Ménibus, Emir Demirović, M.L. Flippo, K. Sidorov, J.E.A.P. Decouchant
This paper presents a new greedy heuristic to extend SAT Solvers when solving the Preemptive resource-constrained project scheduling problem (PRCPSP-ST). The heuristic uses domain-specific knowledge to generate a fixed order of variable selection. We also extend previous work into encoding PRCPSP-ST by providing an alternative upper bound. The heuristic was tested against VSDIS on the J12 dataset. These experiments show that it performed, on average, six times slower than VSDIS.
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This paper presents a new greedy heuristic to extend SAT Solvers when solving the Preemptive resource-constrained project scheduling problem (PRCPSP-ST). The heuristic uses domain-specific knowledge to generate a fixed order of variable selection. We also extend previous work into encoding PRCPSP-ST by providing an alternative upper bound. The heuristic was tested against VSDIS on the J12 dataset. These experiments show that it performed, on average, six times slower than VSDIS.