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Intelligent CG Making Technology and Intelligent Media

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Intelligent CG Making Technology and Intelligent Media ITE Trans. on MTA Vol. 1, No. 1, pp. 20-26 (2013) Copyright © 2013 by ITE Transactions on Media Technology and Applications (MTA) Intelligent CG Making Technology and Intelligent Media Masayuki Nakajima† (member) Abstract In this invited research paper, I will describe the Intelligent CG Making Technology, (ICGMT) pro- duction methodology and Intelligent Media (IM). I will begin with an explanation of the key aspects of the ICGMT and a definition of IM. Thereafter I will explain the three approaches of the ICGMT. These approaches are the reuse of animation data, the making animation from text, and the making animation from natural spo- ken language. Finally, I will explain current approaches of the ICGMT under development by the Nakajima lab- oratory. Keywords: Intelligent, CG, reuse, agent, language understanding 1. Introduction 2. What is Intelligence in CG Computer Graphics (CG) is a technique used to create In this chapter, I introduce the technology supporting images and animation using computer and graphics the Intelligence in CG and thereafter I will define peripheral devices. CG has become a popular medium for Intelligent Media, (IM). science, industrial manufacturing, animation, games, 2.1 Intelligent CG Making Technology (ICGMT) communication and medical visualization. Formally, The term of "Artificial Intelligence" or AI is often used Large-scale investments in technology, skilled personnel to describe the intelligence of machines and the branch and large time allotments were necessary to produce CG of computer science that aims to create intelligence in animation. However, due to developments in Motion ways that emulate some functions of the human brain. Capturing Systems, the KINECT and other motion However "Intelligence" in CG animation differs from acquisition systems, the production of CG animation has this. Intelligence in CG means that the computer aids become faster, easier and less expensive. production efficiently, comfortably and more Furthermore, as a result of recent advances in render- practically1). Furthermore, intelligence in CG includes ing technologies, it is now possible to produce high quali- the domain of KANSEI, which adds sensitivity and feel- ty CG animation that is difficult to distinguish from live- ings. The following five aspects provide a definition of action footage. We can conclude that CG animation is the intelligent CG image production concept. nearing technical completion as it becomes indistin- (1) Production is more readily available to wider user guishable from reality. groups without previous animation skills giving them It can be concluded that in a post-realism era, CG the ability to make high quality CG animations. engineers are struggling to find new ways to further (2) We can generate animation in more ergonomically develop the field. This paper proposes that the key designed environments providing pleasant work- aspects for the future development and facilitation of CG flows and generally a more pleasant experience production are AI (Artificial Intelligence) and Pattern thus allowing animators to concentrate on other Recognition. This invited paper introduces a new AI-like elements such as directing. trial as proposed primarily by Nakajima laboratory. (3) Correspondence with diversification. The system corresponds with 2D, 3D and four- dimensional aspects of representation on both Received September 19, 2012; Revised October 4, 2012; Accepted mobile devices and large high-resolution screens. October 12, 2012 † Gotland University (Sweden) and Director of Center for the Study of (4) Delivery of high resolution graphics providing World Civilization in Tokyo Institute of Technology increased artistic freedom with high fidelity anima- 20 Invited Paper » Intelligent CG Making Technology and Intelligent Media tion for abstraction or realism. data is low-level intelligence and the use of natural lan- (5) Optimized and semi-automated production is pro- guage is high-level intelligence due to the use of lan- viding shorter production periods at less cost. guage recognition technologies. This allows non-skilled users to make CG animation 3.1 Reuse in the Animation Production cheaply and easily. This section introduces advancements in the reuse of Demands in hardware and software specifications data and assets in animation production, as developed require faster computer processing, user-friendly graph- by the Nakajima laboratory2). We have two approaches ics and high-level peripheral devices. In software tech- in animation production. One is making animation nology the following should be taken into consideration: though the production of new assets and another is mak- (1) Advanced image information processing technologies. ing animation by reusing existing animation sequences (2) Advanced image expression and direction technolo- and assets. gy incorporating KANSEI processing, (aesthetic Making animation through the asset production has expression and entertainment). been a branch standard, however reuse is new concept in 2.2 Intelligent CG Production Technology CG production. There are two ways of reuse. The first is The following (1)-(7) technologies are the important reusing the movement data of characters, the other is image information processing. the reuse of the animation sequence itself. These are (1) Database Technology. described as follows. Database Technology is fast enough to retrieve ade- (1) Reuse of Motion Data. quate image information. The main approach for the reuse of motion data is the (2) Computer Vision Technology. reuse of the actual motion data itself. Computer Vision (CV) Technology is effective for mod- (a) Reuse of MOCAP Data. eling of real human and animal movement and for the The most standard approach for the reuse of generation of corresponding animations. MOCAP(Motion CAPture) is the application of the (3) Automatic Language understanding Technology. MOCAP data for reuse in several characters3). And refer- Technical capability of generating animation effective- ence4) is the interactive and hierarchical motion editing ly from both written and spoken language. system of humanoid character movement using MOCAP (4) Human Interface Technology. data. We proposed MOTION BELT5) for the reuse of The development of a user-friendly CG making sys- MOCAP data effectively and visually. tem. (b) Using Motion Graph. (5) Standardization Technology. When we reuse MOCAP data, Motion Graph is used The use of standardization technology, allows us to oper- for the connection of several groups of MOCAP data. ate equally between multiple platforms and projects. Kovar6) is proposed as an automatic Motion Graph gen- (7) The Expert System. eration method from the MOCAP data. This detects the We can make animation, by reusing animation assets, adequate movement from the Motion Graph and gener- which are designed and made by experts in the field. ates the connection pass between two Motion Graphs. We can state "Intelligent Media" (IM) is created (c) Combination with the Key Frame Animation through the development of the Intelligent CG Making Method. Technology (ICGMT) production methodology. These One of the approaches is the generation of Key frame technologies offer new advances towards the develop- animation from several kinds of MOCAP data7). In this ment of future trends of media production providing paper, we can also add exaggeration of movement in optimized high-level animations. selected key frames of the animation to improve the expressive quality. 3. Trial of the Intelligent CG Making System (2) Reuse of Animation Scenes and Image Data. In this chapter, I will describe examples of the intelli- A widely used method in production for weekly televi- gent CG (image and animation) making research papers. sion programs is the pre-vis checking of the character 3.1 describes the reuse of animation data, 3.2 describes motion in the early stages of production. This allows for making animation from Text and 3.3 describes the mak- adjustments to be made early on, preventing irregulari- ing of animation through the use of natural language. ties later in production. In consideration of this, it is It should be pointed out that the reuse of animation important for the industry to be able to reuse existing 21 ITE Trans. on MTA Vol. 1, No. 1 (2013) animation sequences to produce new animations directly and effectively without irregularities of motion. (a) Method of Making Reusable. To make existing sequences reusable, it is necessary to extract the motion at the same time as the extraction of the model shape from the animation. To achieve this, Fig.1 The structure of the system implemented with the use of we used pattern matching and structural matching algo- the 'Reuters' website. rithms for previous animation sequences2). The match- ing process is as follows: (I) Binarization and Line Approximation. speaks by the use of a synthetic voice. In addition, the The bitmap image from a frame of a 2D animation studio shot can control all camera positioning and move- sequence is finalized and the lines of model shape are fila- ment as well as all lighting. In addition, all postproduc- mented. Because the image is drawn using lines, theses tion processing and compositing used in TV programs, lines can be transferred and reformed in several characters. BGM, and movie productions, are also facilitated in the (II) Extracting Lines. TVML player in real-time. The line of a sequence is extracted by detecting inter- (2) T2V System section points and start and end points. We proposed T2V (Text-To-Vision)
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