Holographic stereogram printing based on digitally computed content generation platform

2019 ◽  
Author(s):  
Erkhembaatar Dashdavaa ◽  
Anar Khuderchuluun ◽  
Young-Tae Lim ◽  
Seok-Hee Jeon ◽  
Nam Kim
Keyword(s):  
Holographic Stereogram ◽  
Content Generation

Simplified digital content generation based on an inverse-directed propagation algorithm for holographic stereogram printing

2021 ◽  
Author(s):  
Anar Khuderchuluun ◽  
Yan-Ling Piao ◽  
Munkh-Uchral Erdenebat ◽  
Erkhembaatar Dashdavaa ◽  
Moung Hee Lee ◽  
...  
Keyword(s):  
Digital Content ◽  
Propagation Algorithm ◽  
Holographic Stereogram ◽  
Content Generation

Social Network Integration and User Content Generation: Evidence from Natural Experiments

MIS Quarterly ◽  
2017 ◽  
Vol 41 (4) ◽  
pp. 1035-1058 ◽  
Author(s):  
Ni Huang ◽  
◽  
Yili Hong ◽  
Gordon Burtch ◽  
◽  
...  
Keyword(s):  
Social Network ◽  
Natural Experiments ◽  
Network Integration ◽  
User Content ◽  
Content Generation

Island Generator pada Game Open world Menggunakan Algoritma Perlin noise

Repositor ◽  
2020 ◽  
Vol 2 (7) ◽  
pp. 965
Author(s):  
Naufal Azzmi ◽  
Lailatul Husniah ◽  
Ali Sofyan Kholimi
Keyword(s):  
Performance Testing ◽  
Game Development ◽  
Procedural Content Generation ◽  
Open World ◽  
Game World ◽  
Perlin Noise ◽  
And Performance ◽  
Game Developers ◽  
Pcg Method ◽  
Content Generation

AbstrakPerkembangan game pada saat ini berkembang dengan sangat cepat, dalam perkermbangan game topik AI adalah topik yang paling banyak diteliti oleh beberapa peneliti khususnya pada pembuatan suatu konten game menggunakan metode PCG (procedural content generation). Pada pembuatan sebuah game world menggunakan metode PCG sudah banyak developer game yang sukses dengan mengimplementasikan metode ini, metode ini banyak digunkan pada geme dengan genre RPG, Rouglikes, Platformer, SandBox, Simulation dan lain sebagainya, Pada penelitian ini berfokus pada pengembangan sebuah game world generator untuk game berjenis open world yang berupa sebuah kepulauan dengan metode PCG dengan menggunakan algoritma perlin noise sebagai algoritma pembentuk textur utama pulau yang dimana pada penelitian ini memanfaatkan beberapa variable noise seperti octave, presistance dan lacunarity guna untuk menambah kontrol dari hasil textur yang dihasilkan serta algoritma penempatan pulau untuk membuat sebuah game world yang menyerupai sebuah kepulauan. Dari hasil uji generator terkait degan pengujian playability dan performa dapat disimpulkan bahwa generator yang dikembangkan playable serta performa yang dianaliasa menggunakan notasi Big O menunjukkan  (linear). Abstract Game development is currently growing very fast, game development AI is the most discussed topic by most researchers especially in the developing of game content using the PCG (procedural content generation) method. In making a game world using the PCG method, many game developers have succeeded by implementing this method, this method is widely used on RPGs, Rouglikes, Platformers, SandBox, Simulations and ect,. This study focuses on developing a game world generator game for open world type games in the form of an archipelago using the PCG method using the noise perlin algorithm as the island's main texturizing algorithm which in this study utilizes several noise variables such as octave, presistance and use for add control of the texture results as well as the island placement algorithm’s to create a game world that resembles an archipelago form. From the generator test results related to the playability and performance testing, it shows that map are being generated by the generators are playable and performance that are analyzed using Big O notation show O (n) (linear).

scholarly journals Deep learning for procedural content generation

2020 ◽  
Author(s):  
Jialin Liu ◽  
Sam Snodgrass ◽  
Ahmed Khalifa ◽  
Sebastian Risi ◽  
Georgios N. Yannakakis ◽  
...  
Keyword(s):  
Deep Learning ◽  
Procedural Content Generation ◽  
Content Generation

scholarly journals Internet of Vehicles Empowered Mobile Media: Research on Mobile-Generated Content (MoGC) for Intelligent Connected Vehicles

2021 ◽  
Vol 13 (6) ◽  
pp. 3538
Author(s):  
Zhiyuan Yu ◽  
Doudou Jin ◽  
Chao Zhai ◽  
Wan Ni ◽  
Desheng Wang
Keyword(s):  
Production Capacity ◽  
Professional Organizations ◽  
Connected Vehicles ◽  
New Production ◽  
Mobile Media ◽  
Internet Of Vehicles ◽  
News Source ◽  
Media Environments ◽  
Content Generation

With the rapid growth of mobile media, large quantities of mobile content have been generated by moving entities. Some content generation patterns become popular for users and professional organizations, e.g., user-generated content, professionally-generated content, machine-generated content. However, due to the limitations of device types and functions, it is necessary to explore the new production tools and further inspire the content potential in mobile scenarios. According to the production capacity supported by Internet of Vehicles, intelligent connected vehicles (ICVs) emerge as new content generated devices in sustainable cities. In this paper, we propose the concept of Mobile-Generated Content (MoGC) as a new part of production patterns. First, we analyze the relationship between MoGC and existing patterns from the perspectives of entity and workflow. Second, the unique functionality and social property of MoGC are revealed, i.e., ICVs play the role of middle platform with data and technology offices. The current dominant discourse created by the professional institutions (e.g., media agency or governing authority) will transfer to the vehicle users. In this way, the content generation system has been further enriched in omni-media environments through efficiently integrating productivity tools and resources. Besides, MoGC not only contributes to social governance by enlarging the news source and coverage, but also strengthen the personal discourse in mobile scenarios.

Procedural content generation for games

2013 ◽  
Vol 9 (1) ◽  
pp. 1-22 ◽  
Author(s):  
Mark Hendrikx ◽  
Sebastiaan Meijer ◽  
Joeri Van Der Velden ◽  
Alexandru Iosup
Keyword(s):  
Procedural Content Generation ◽  
Content Generation

3-D Construction of Imaginary Objects by the Method of Holographic Stereogram

1971 ◽  
pp. 19-34 ◽  
Author(s):  
Tadashi Kasahara ◽  
Yoshiaki Kimura ◽  
Masanori Kawai
Keyword(s):  
Holographic Stereogram
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