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Inferences combine information from the target paper (blue) with the source paper (orange).

Evolving Expression of Emotions through Color in Virtual Humans using Genetic Algorithms (Year 2010) PDF Inferences Show Both PDFs Nehovah: A Neologism Creator Nomen Ipsum (Year 2014) PDF
For centuries artists have been exploring the formal elements of art (lines, space, mass, light, color, sound, etc.) to express emotions. This paper takes this insight to explore new forms of expression for virtual humans which go beyond the usual bodily, facial and vocal expression channels. In particular, the paper focuses on how to use color to influence the perception of emotions in virtual humans. First, a lighting model and filters are used to manipulate color. Next, an evolutionary model, based on genetic algorithms, is developed to learn novel associations between emotions and color. An experiment is then conducted where non-experts evolve mappings for joy and sadness, without being aware that genetic algorithms are used. In a second experiment, the mappings are analyzed with respect to its features and how general they are. Results indicate that the average fitness increases with each new generation, thus suggesting that people are succeeding in creating novel and useful mappings for the emotions. Moreover, the results show consistent differences between the evolved images of joy and the evolved images of sadness.
A system will called a lighting model.

A lighting model will depends a user.

A lighting model will focuses the neologisms from a set of base words provided by a user.

A lighting model will communicate the concept_source.

In this paper, we describe a system called Nehovah that generates neologisms from a set of base words provided by a user. Nehovah focuses on creating " good " neologisms by evaluating various attributes of a neologism such as how well it communicates the source concepts and how " catchy " it is. Because Nehovah depends on the user to weight the importance of various attributes of the neologism and to choose the source concepts, it is at this point most appropriately considered a collaborative system rather than an autonomous one. To demonstrate the utility of the system, we show several examples of system output and discuss the creativity of Nehovah with respect to several characteristics critical for any computational creative system: appreciation, imagination , skill and accountability.

Evolving Expression of Emotions through Color in Virtual Humans using Genetic Algorithms (Year 2010) PDF	Inferences Show Both PDFs	Nehovah: A Neologism Creator Nomen Ipsum (Year 2014) PDF
For centuries artists have been exploring the formal elements of art (lines, space, mass, light, color, sound, etc.) to express emotions. This paper takes this insight to explore new forms of expression for virtual humans which go beyond the usual bodily, facial and vocal expression channels. In particular, the paper focuses on how to use color to influence the perception of emotions in virtual humans. First, a lighting model and filters are used to manipulate color. Next, an evolutionary model, based on genetic algorithms, is developed to learn novel associations between emotions and color. An experiment is then conducted where non-experts evolve mappings for joy and sadness, without being aware that genetic algorithms are used. In a second experiment, the mappings are analyzed with respect to its features and how general they are. Results indicate that the average fitness increases with each new generation, thus suggesting that people are succeeding in creating novel and useful mappings for the emotions. Moreover, the results show consistent differences between the evolved images of joy and the evolved images of sadness.	A system will called a lighting model. A lighting model will depends a user. A lighting model will focuses the neologisms from a set of base words provided by a user. A lighting model will communicate the concept_source.	In this paper, we describe a system called Nehovah that generates neologisms from a set of base words provided by a user. Nehovah focuses on creating " good " neologisms by evaluating various attributes of a neologism such as how well it communicates the source concepts and how " catchy " it is. Because Nehovah depends on the user to weight the importance of various attributes of the neologism and to choose the source concepts, it is at this point most appropriately considered a collaborative system rather than an autonomous one. To demonstrate the utility of the system, we show several examples of system output and discuss the creativity of Nehovah with respect to several characteristics critical for any computational creative system: appreciation, imagination , skill and accountability.

Key Mapped Terms

Target Node Source Node
color_result point
base focus
be show
focus consider
humans_themselves system
be be
association \"\"
model nehovah_it_system_its
be be
[unknown]-0 example

Target Node	Source Node
color_result	point
base	focus
be	show
focus	consider
humans_themselves	system
be	be
association	\"\"
model	nehovah_it_system_its
be	be
[unknown]-0	example

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