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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Robustifying SLAM using multiple cameras / Mer robust SLAM med flera kameror

Sillén, Erik January 2016 (has links)
This master thesis is about modifying a certain monocular visual SLAM algorithm to address some of its limitations. The SLAM algorithm is not robust to quick camera motions and input images in which there are few visible features. A second camera and an inertial measurement unit was added to the hardware. Then a method for selecting the appropriate camera for tracking depending on the estimated number of features was implemented to solve the issue of few features. Experiments and results show that this method works well for slow motions. A gyrometer threshold method along with a motion model to solve the issue of quick motions was implemented and reviewed in this thesis. / Detta examensarbete handlar om att ta itu med några begränsningar som en viss monokulär visuell SLAM-algoritm har. SLAM-algoritmen är inte robust mot snabba kamerarörelser och indatabilder som innehåller få karaktärsdrag. Genom att introducera en extra kamera, en accelerometer och en gyrometer, behandlas dessa problem i denna rapport. En metod för att välja kamera att hämta indatabilder från, baserat på det skattade antalet karaktärsdrag i respektive bild implementerades. Denna metod är tänkt att lösa problemet då indatabilder har få karaktärsdrag. Experiment visar att denna metod fungerar bra för långsamma rörelser. En metod som jämför gyrometerdata med ett tröskelvärde tillsammans med en rörelsemodell implementerades för att lösa problemen vid snabb rörelse. Dessa metoder undersöks och diskuteras i rapporten.
2

Reducing animator keyframes

Holden, Daniel January 2017 (has links)
The aim of this doctoral thesis is to present a body of work aimed at reducing the time spent by animators manually constructing keyframed animation. To this end we present a number of state of the art machine learning techniques applied to the domain of character animation. Data-driven tools for the synthesis and production of character animation have a good track record of success. In particular, they have been adopted thoroughly in the games industry as they allow designers as well as animators to simply specify the high-level descriptions of the animations to be created, and the rest is produced automatically. Even so, these techniques have not been thoroughly adopted in the film industry in the production of keyframe based animation [Planet, 2012]. Due to this, the cost of producing high quality keyframed animation remains very high, and the time of professional animators is increasingly precious. We present our work in four main chapters. We first tackle the key problem in the adoption of data-driven tools for key framed animation - a problem called the inversion of the rig function. Secondly, we show the construction of a new tool for data-driven character animation called the motion manifold - a representation of motion constructed using deep learning that has a number of properties useful for animation research. Thirdly, we show how the motion manifold can be extended as a general tool for performing data-driven animation synthesis and editing. Finally, we show how these techniques developed for keyframed animation can also be adapted to advance the state of the art in the games industry.
3

The Art Of The Walk Cycle : Animating Emotions with Artistic Expression

Ghazali, Rania January 2024 (has links)
This exploration delves into the potential of emotional storytelling through walk cycles. Moving beyond traditional animation, it utilizes the expressive power of modern tools to explore how line, shape, stroke weight, color, texture, and sound can be manipulated to create abstract narratives that evoke deeper emotional experience for the viewer.  Drawing on a foundation of psychological principles, scientific research, and relevant articles, the walk cycles become abstract narratives, provoking introspection and emotional connection. The subjective nature of this artistic language is acknowledged, with cultural backgrounds and personal experiences influencing interpretation. The exploration raises questions about the potential for a universal language of emotion in animation, one that speaks not just to the mind, but to the heart. This ongoing journey of discovery aims to observe how viewers connect with these abstract representations and explore the potential for this approach to elevate the art of animation.

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