Hyper-Realist Rendering: A Theoretical Framework

arXiv (Cornell University) · 2024 · 1 citations

• Computer Science
• Artificial Intelligence
• Computer Science

This is the first paper in a series on hyper-realist rendering. In this paper, we introduce the concept of hyper-realist rendering and present a theoretical framework to obtain hyper-realist images. We are using the term Hyper-realism as an umbrella word that captures all types of visual artifacts that can evoke an impression of reality. The hyper-realist artifacts are visual representations that are not necessarily created by following logical and physical principles and can still be perceived as representations of reality. This idea stems from the principles of representational arts, which attain visually acceptable renderings of scenes without implementing strict physical laws of optics and materials. The objective of this work is to demonstrate that it is possible to obtain visually acceptable illusions of reality by employing such artistic approaches. With representational art methods, we can even obtain an alternate illusion of reality that looks more real even when it is not real. This paper demonstrates that it is common to create illusions of reality in visual arts with examples of paintings by representational artists. We propose an approach to obtain expressive local and global illuminations to obtain these stylistic illusions with a set of well-defined and formal methods.

An Interactive Web-Based System for Creating Single Panel Cartoons with Visually Valid Compositions

arXiv (Cornell University) · 2023

• Computer Science
• Computer Science
• Artificial Intelligence

The creation of cartoon-based stories (comics) requires a lot of creativity and hard work for naive users. We observe that single-panel cartoons are the building blocks of any comic story. To develop a strong comic story, it is critical to obtain visually valid single panels. In this work, we have developed a methodology to guarantee the placement of characters to obtain a valid cartoon frame based on the methods used by professional cartoonists. Using this methodology, we have developed a web-based system to create single-panel cartoons from a given set of character images. We have made this system available in GitHub as open-source so that this basic single-panel cartoon can be used as infrastructure to develop more complex structures. Our web-based system for single-panel cartoons can be viewed at http://storytelling.viz.tamu.edu.

Causality Effects of Interventions and Stressors on Driving Behaviors under Typical Conditions

Mathematics · 2018-08-14 · 8 citations

In this paper, we demonstrate that interventions and stressors do not necessarily cause the same distractions in all people; therefore, it is impossible to evaluate the impacts of interventions and stressors on traffic accidents. We analyzed publicly available multimodal data that was collected through one of the largest controlled experiments on distracted driving. A crossover design was used to examine the effects of actual and perceived interventions and stressors in driving behaviors and parallel designs on reactivity to a startling event. To analyze this data and make recommendations, we developed and compared a wide variety of mixed effects statistical models and machine learning methods to evaluate the effects of interventions and stressors on driving behaviors.

Obtaining Four Main Animation Cycles Using an Extremely Limited Set of Poses

2017-01-01

A Theoretical Framework to Represent Narrative Structures for Visual Storytelling

2015-01-01 · 4 citations

In this paper, we present a theoretical framework to represent and manipulate narrative structures for visual storytelling. This framework can be used in applications beyond visual storytelling, which includes formal representation of stories, emotional, social and even economical interactions among agents. Our framework significantly extends and formalizes classical narratology theories. In our framework, we represent narratological functions as interventions by employing an extension of causal inference theory, as directed graphs that provide cause and effect relationships among agents. Moreover, we categorize them as real, expressed and observed interventions. This differentiation allows us to represent beliefs, lies and misunderstandings. In our framework, any transformation in causality graph structure is called an event by providing a non-linear temporal dimension that can even allow timetravel. This approach provides a general framework to develop tools for modeling narration and can help to investigate social and economic interactions.

Farm Prices, Retail Prices, and Directed Graphs: Results for Pork and Beef

American Journal of Agricultural Economics · 1998-12-01 · 119 citations