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Tinjauan Historis Kecerdasan Buatan Dalam Games Troy, Troy
Journal of Animation & Games Studies Vol 1, No 2 (2015): Oktober 2015
Publisher : Institut Seni Indonesia Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (688.219 KB) | DOI: 10.24821/jags.v1i2.1302

Abstract

Video games experienced rapid development in terms of gameplay, level of difficulty, and artificial intelligence. Artificial intelligence in computer games devoted to the ability to control the elements in the game that make intelligent decisions when a state has several options with different outcomes, resulting in behaviors that are relevant, effective, and useful. In the video game, scoring as well as compliance with the rules and visual display is presented by computers, not by humans. Computers also control the enemy character in the game, becoming another participant, acting as referee, as well as the condition of an area "game". This paper will discuss the development of artificial intelligence in video games in terms of gameplay, the level of difficulty and the development of video game device.Keywords: video games, artificial intelligence, history, gaming devices.AbstrakVideo game mengalami perkembangan yang pesat dari sisi gameplay, tingkat kesulitan, dan kecerdasan buatan. Kecerdasan buatan pada game dikhususkan pada kemampuan komputer mengendalikan unsur-unsur dalam game yang membuat keputusan cerdas ketika suatu kondisi memiliki beberapa pilihan dengan hasil akhir yang berbeda, sehingga menghasilkan perilaku yang relevan, efektif, dan berguna. Dalam video game, pemberian nilai serta kepatuhan terhadap aturan dan tampilan visual disajikan oleh komputer, bukan oleh manusia. Komputer juga yang melakukan kontrol karakter musuh dalam permainan, menjadi peserta lain, bertindak sebagai wasit, serta mengkondisikan suatu area “permainan”. Pada paper ini akan dibahas mengenai perkembangan kecerdasan buatan dalam video game dari sisi gameplay, tingkat kesulitan dan perkembangan perangkat video game.Kata kunci: video game, gameplay, kecerdasan buatan, sejarah, perangkat game.
Transformasi Ruang 2D Ke 3D Pada Animasi Wajah Berbasis Data Marker Menggunakan Radial Basis Function Troy, Troy; Pranowo, Pranowo
Journal of Animation & Games Studies Vol 2, No 2 (2016): Oktober 2016
Publisher : Institut Seni Indonesia Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (5787.872 KB) | DOI: 10.24821/jags.v2i2.1422

Abstract

Computer facial animation aims to create an animated character expression as natural as possible as well as human facial expressions. Using the data marker catches facial motion capture, will be determined the location of the feature points of 3D face models to follow the motion of the marker points of human faces.To overcome the morphological differences between the face of the source with the character's face, then applied with radial basis retargeting process mapping so that the character's face can still display the natural expression. Using the data marker 2D, Radial Basis Function (RBF) space transformation was applied to determine the position of the feature points on the 3D face models.RBF space transformation has good ability in determining the appropriate facial motion marker points on a human face to the character's face. Motion that occurs in 3D face models is scaled according to the relative scale between the source and the target. Keywords: facial animation, radial basis function, marker data. AbstrakTeknik komputasi yang dikembangkan pada animasi wajah bertujuan untuk menciptakan ekspresi pada wajah karakter animasi senatural mungkin seperti layaknya ekspresi pada wajah manusia. Menggunakan data marker pada citra 2D wajah manusia, komputer menangkap pergerakan marker tersebut kemudian menetukan lokasi titik fitur yang pada wajah model 3D (karakter animasi).Untuk mengatasi perbedaan morfologi pada wajah manusia yang menjadi sumber acuan ekspresi dengan wajah model 3D yang menjadi target animasi, maka diterapkan transformasi ruang Radial Basis Function (RBF). RBF digunakan untuk menentukan posisi titik fitur pada wajah model 3D berdasarkan posisi titik marker pada citra 2D wajah manusia.Transformasi ruang RBF memiliki kemampuan yang baik dalam pemetaan ulang titik marker dari wajah manusia ke titik fitur pada wajah karakter animasi. Pergerakan yang terjadi pada wajah model 3D berdasar pada skala relatif antara titik marker pada citra 2D wajah manusia dengan titik fitur pada wajah model 3D.Kata kunci: animasi wajah, radial basis function, data marker.
Evaluasi Sintesis Ekspresi Wajah Realistik pada Sistem Animasi Wajah 3D dengan Teknologi Motion Capture Gunanto, Samuel Gandang; Sulistiyono, Arif; Atmani, Agnes Karina Pritha; Troy, Troy
REKAM: Jurnal Fotografi, Televisi, dan Animasi Vol 14, No 2 (2018): REKAM
Publisher : Institut Seni Indonesia Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1165.295 KB) | DOI: 10.24821/rekam.v14i2.1747

Abstract

The human face has a unique shape and size, as well as a 3D character face model. The facial animation of 3D virtual characters is mostly done manually by moving the rigging in each frame. The more characters used, the more production costs that must be incurred. The absence of a cheap facial motion transfers system is also one of the reasons why not many studios are using motion capture technology in Indonesia.This research will evaluate the implementation of a facial expression synthetically using motion capture technology built from radial basis function (RBF) as a method of marker transfer as a reference for rigging movement in point cluster system. Testing is done by approaching facial expressions according to FACS theory and questionnaire of synthesis results.The experimental results show that according to FACS theory the requirement of expression formation has been fulfilled by referring to changes in facial features, but the implementation is not always able to describe perfectly the desired condition, namely the average percentage of faces easily recognizable by 35.53%. Therefore, the influence of animators in the control of micro expression improvements or the addition of exaggeration principle elements in the manufacture of facial animation is very important to produce facial expressions that are easily recognized by the audience.