CONTEXT

Post by 
Oleg Efimov
Published 
In the character driven narratives actor’s performance is the heart and soul that makes audiences to be attentive and drawn towards the medium. Primarily facial performance in cinematic narrative creates an emotional bond between digital reality and human perception. People’ emotions have the phenomena of being reflected and resonated with in daily interactions, character on the screen and the audience that experiencing it. In digitally generated world the emotional intention is energetically concentrated when it comes to deliver performer’s soul which is done with facial motion capture systems. This text uncovers the concepts of the practical craft created using high end motion capture approach from theoretical, methodological and technical angles with expanded examples and references for various sources relevant to the study of such phenomena as the human face. Application and practical use of this knowledge is primarily relevant to feature film productions and visual effects but also to medical visualisation, cosmetic surgery and criminalistic investigations. Theoretical framework of the craft is dedicated to study of the human basic emotions, cyber-synthetic underpinnings, digitally generated humans and simulated reality. Methodology is orbiting around different approaches whether it is better to use motion capture technology or traditional key frame animation. Discovering different motion capture systems and crossing critical line between them by shifting the force towards high quality standards reflected in feature film Avatar (J.Cameron, 2009). The scanning of the human face is investigated as a method including dynamic mesh deformation capture. Lastly this document is dedicated to explore the innovative algorithms in performance capture and possible future in the field of research. Dealing with fundamental principles for building digital human marionette system, ways of enhancement by focusing on the local and the most influential facial feature which is the human eye. The technical area is concluded with investigation and observation of many valuable resources that are in the arsenal for successful goal-oriented outcome. This is grounded with experience and knowledge which came out of the research and development that were put on the line within the timeframe of this project and reflected in the conclusion.

Synopsis: “Air force pilot intelligence officer Sandy experiences identity transformation after realising she has been artificially built and controlled by a cybernetic existence.”

Theoretical layer is critically associated with historical visions of the future and cyber-synthetic approach. Highly influenced by the science fiction motion pictures such as “Avatar” (J.Cameron, 2009), “The Matrix” (Larry and Andy Wachowki, 1999) and “The Ghost in the Shell” (Mashimoru Oshii, 1995) where the mix of the human DNA and mechanical nature is contextually represented. Those texts are icons of a deeper theme in science fiction literature, ideas where the new area of information such as biomechanics and cybernetics arose. Cyber culture is dealing with the fear of an unseen, virtual enemy, results of genetic engineering, ecological destruction, exponential growth and inflation of technology into the daily life. Manly the driven theme of the narrative is the fear of losing control over life and giving the power away to machines. Connecting fear with the field of emotion which is the key in facial performance this project is aiming to bring the uncanny feeling by creating a confrontational paradox between attraction and fear. This comes down to the character herself who are the twenty two year old female, a hero awaken from the artificially controlled dream. The fact of being awake is not unique and yet cyclic where the machine does systematically reformat her memory cluster. This brings us to the heart of the theoretical soul for this text in which is the question of identity.

Motoko: “Just as there are many parts needed to make a human a human, there is a remarkable number of things needed to make an individual what they are. A face distinguish yourself from others. The memories of childhood, the feelings for the future. All of that goes into making me what I am.“ (Mashimoru Oshii, 1995).

Beside identity and deep personal transformation the area of knowledge that also carries the research is virtual reality and the creation of digital humans. These are relevant to simulation, training, education, artificial intelligence, entertainment, mixed-reality, virtual or digital anatomy including virtual patients. The creation of an anatomically motivated digital human head includes the face allowing the complete control over subtle shape that the face can express. There is a database of not only every possible clear frozen emotional expression but also the full range of combinations of those pro-mutated basic expressions. This comes down to the fact that humans never express and feel the experience of one particular emotion. Usually its is a combination of emotions based on various factors such as first or second-hand experience, recent interactions and things that shape human identity far deep in childhood including the evolutional experience of human population.

Furthermore seeing emotions as the effect and not a cause of things, not only internal and global reasons stand behind our emotions, physical conditions of light brightness, direction and intensity, air temperature, perceived visuals and sounds can cause particular or expected emotions in addition to the reaction to events. This knowledge become powerful for controlling or manipulating masses not only from the entertainment point of view but from political, military and medical origins. The parallel line between emotional knowledge and artificial intelligence can be easily crossed with the fact that we are not aware of where humans came from and how the world was shaped. In human history, people were many times wrong about some beliefs. People were thinking that the planet is flat. Probably even today we are wrong about something and artificial intelligence is what already control our lives. The knowledge about real world experience and phenomenas can change the way we see and operate in every day life with letting it come through us will make you never look at the human face in the same fashion ever again.

Speaking from methodological angle there are two main approaches in the field of digitally generated performance of virtual actors which are the traditional key frame animation and performance driven motion capture technology. Having as highly successful and relevantly recent examples from popular culture films like “Avatar” (J.Cameron, 2009) and “Rise of the Planet of the Apes” (R.Wyatt, 2011) where facial motion capture technology was used and found potential success ground the priority of the methodological approach was directed towards facial image- based motion capture technology that naturally translates emotional intent and soul of an actor into digital reality using various technical systems whether or not using reflective passive or active markers placed on character’s face, markerless video based algorithms or luminescent glowing powder for scanning the entire surface of the face. However the approach of traditional key frame animation was practiced as well with complete failure in relation to the balance of quality and time resourcefulness. Having a captured from real life performance data will confidently allow to explicit that the animation stage of digital production will be handled far more faster than traditional key framing technique. This is explained by limited possibilities of human resources to approach computer animation by studying it, practicing and mastering where the informational database created by captured performance from real life will provide the first layer or skeleton of point movement. Before going even more technical the second methodological dilemma was to choose of what exact type of facial motion capture to choose from in order to deliver highly realistic, believable and convincing results and jump out of animation category into feature film level. Being in academic environment put limitations to access to those systems due their complexity and costly prices. Its not a secret that facial animation is the advanced topic at ACM SIGGRAPH, the computer graphics and interactive communities and only award winning visual effects or production houses have access to those systems and publications around that subject. In this case there were two systems were available for this craft the Optical Motion Capture System and tracking software Optitrack for facial motion capture purchased by Auckland University of Technology in 2011 and recently presented to market the innovative Facial Animation Software: Performance Driven Animation Technology – Faceware developed by leading facial animation company the Image Metrics. Two different systems, with using markers and markerless video based. For this particular project was used Faceware due to proven results and simplistic approach with more believable and convincing results. This statement is arguable due to the complexity of facial animation workflow in general where the quality of captured data is not the key to successful digital performance but marionette rigging system that allows to control facial features as closely as possible to reality. Passing the point of saying that Faceware allows to construct successful and relatively rapid workflow of facial motion capture and underline that Optitrack systems can also be utilised for high quality results with bringing more effort to digital marionette craftsmanship stage. It is crucial to explore other and more high end solutions in this field where this project can be pushed in future.

The “Mova CONTOUR Reality Capture is markerless high-resolution facial capture, cost-effectively providing photoreal 3D faces for games and visual effects.”

This technology uses luminescent powder sprayed on an actor’s face where optical triangulation similarly to three dimensional scanning approach and captured by infrared cameras shooting from various angles in relation to the face. This provides with high fidelity data of entire face surface that changes in time based on the actor performance which allows to construct a three dimensional model referencing the given surface. This technology was used in the feature film “The Curious Case of Benjamin Button” (D.Fincher, 2008) that got three academy awards titled Best Visual Effects, Best Directing and Best Makeup. Final fundamental and the most advanced method that was developed and used in visual effects company Weta Digital in New Zealand which was used in film Avatar (J.Cameron) with non countable awards and premium digital facial performances that would be the next level of pushing this project forward. Prime focus is to create an outstandingly complex rigging system that is triggered by limited amount of facial markers placed on the face and creation scriptable expressions that drive the rest of organic material as it happens in real life. The use of markers allows to keep three dimensionality and depth of human face as well as having possibility not to be depended on light conditions. In this case the placement of individual marker on the face is caused by location of power points of where dynamic forces of nerves are pushing or pulling facial muscles, tissues underneath facial skin, fat and other constructive elements of the human face. For this approach the approximate minimum amount of facial markers is about five hundred which allows to achieve medically and bio mechanically proven believable performance. This method is the direction of where this project will lead in future and post graduate studies.

As per methodology already technically this project is very complex however it is very crucial to hit the main key points of important tactics and techniques that will allow to solve problems before they even arise. There are three main components in technical evaluations which firstly is revolutional and innovative algorithm developed by the Image Metrics and possible future of it. Second is facial rigging system which is the key to success in the whole facial performance workflow, ways and methods of approaching it, pluses and minuses of any particular system and ways of enhancement. Third is where the actual clear cut future of this body of knowledge and practice will lead in the space of next two years. The Image Metrics product called Faceware made this project possible due to the fact that it allowed to have an industry standard high fidelity facial performance capture data that will drive any type of facial rig based on video analysis that does not need any marker to be placed on an actor face. Firstly, it highly attracts actors to do the role due to the fact that people definitely skeptical about placing anything on their faces and secondly and more significantly this makes the acting be more natural, believable and convincing, because with the use of markers, actors have to overcome the fact of marker existence but physically they are still there. That makes the performance limited by the inconvenience of having markers all over the face. This algorithm is based on defining particular areas of the face and breaking those into three main groups such as brows, eyes and mouth. Then defining points and depth of those based on the video reference and calculate the path on the frame by frame basis of where those points travel. This provides with flawless energy that comes through the capture and later being applied to facial rigging system which provides with heart rate like density of data that comes through digital actor or if you like fuels him/her with a soul.

“FACEWARE – The technology that captures the soul.” (New York Times)

In terms of facial motion capture research and development it is literally the revolution because it is markerless and having enough confidence by investigating more than two years in this field it is not a doubt that this is where the facial motion capture will lead to in terms of its future.

Image Metrics was always ahead of the facial animation field with creation the Digital Emily project with breaking uncanny valley belief system which might lead to the possible conclusion that this will be the company that will first come up with solutions of non marker facial capture still maintaining premium quality. Second fundamentally technical realization during the project development was the significance of facial rigging system. At first in order to come up with very rapid and manageable solution there was used an auto rigging system The Facemachine developed by the company Anvozin which allows to create the control system of expressive humanoid face in the space of one hour. This solution is also allows to be driven by any type of performance capture as well as to be used with the technique of traditional key frame animation. Technically speaking it is a cluster deformer based rig that has a certain amount of curves with particular influence areas of the face. Even though it is very easy to use and setup rigging system it does not allow to have phenomenas such as eyelid follow and sticky lips. The bottom line for The Face Machine product is that it is perfect for quick setup and use in animation pipelines but not for feature animation however it could be used as a middle step for having rapid engine of creation morph targets or bled shapes or key poses. The main evaluation of the technical part was to pay more attention to the rigging stage. The fundamental outcome was that the hybrid style rig is the perfect solution for feature film quality. The hybrid rig is the combination of all possible techniques used in facial rigging including a sixty four joint setup inside the character’s head with built in expressions that allows to create relationships that caused by open jaw or eyes being moved to any direction. Also in hybrid rigs the rich amount of blend shapes or key poses are used as well in order to control shapes, thickness and compressions of facial features in the particular time frame. The logic behind generating shapes is grounded on Facial Action Coding System (FACS) crafted by Paul Ekman. From one solution to another the amount of blend shapes differs. From five hundred to couple thousands which allow to have realistic control of the human face. Its all framed with on top cluster deformers that follow the mesh. Finally its all programmed and simplified to a relatively easy to use interface that allow animators to deliver realistic and highly influential performance.

“We each experience the same emotions, but we all experience them differently.” (P.Ekman, Emotions revealed, 2003) Also by Paul Ekman.

Conclusion for this paper about facial performance in cinematic narrative is about two main points. First is future of this research which is the main reflection and evaluation of what was learned, second is the batch of ideas beyond technical, verbal, tangible concepts that have more spiritual nature to them and basically causing the resonation for keeping this project on the same track further and further. Before bringing those two points it is significant to underline that the outcome of this project is the first successful student achievement in facial animation in Australasia and confirms that it was pushed as far as possible in the given time. This project will be continued in postgraduate research with the practical solutions for creation a realistic human eye, replicating behavioral movement of the eye, eyelid follow phenomena, moisture surface of the eyeball, structure of all constructive optical elements such as pupil, lens, iris, eyeball, etc. There will be taken high definition references of the human eye from six various angles using six cameras capturing unique performance simultaneously. As an extension of this current investigation there will be constructed a hybrid style rig that will allow to pose the character in any possible shape that can be shown in digital world from any possible viewport. The prime focus of this investigation is dedicated to the eye area or character’s window to the soul where the double attention will be given to marionette setup that will allow to displace eyelid accordingly to the shape of the eyeball which is not sphere but more of an egg shape, taking into consideration limitations caused by liquids that exist between eyeball and eyelid. Interestingly enough that all those subtle details of the face are not noticeable in everyday life until we become aware of those and start to pay double attention to them, seeing when people actually tell truth or not, feel anger even if they smile and so on and so forth. Thats including animals. Personally speaking when this art investigation was started the author had experienced emotional harm which resonated so much interest to this body of knowledge with practical application to film industry. This project had opened a lot of concepts, ideas and realisations along the road technically but also set free emotional tension and improved emotional life. This is basically what is aimed to do to audiences that come and watch a film using those techniques and knowledge for good, not for harm. Real world and life in general is something that is given to us already and none of the computer systems will have button “Create Human Head” or “Create Planet Earth” unless in close future which means we have to double appreciate the world we live in today and keep it in safe peace and infinitive harmony, no matter what we specialise in.

Reference list

F. PIGHIN, J. HECKER, D. LISCHINSK et al. Synthesizing realistic facial expressions from photographs, Computer Graphics Proceedings, Annual Conference Series, ACM SIGGRAPH, Orlando, 1998, 75-84

Thibos, L.N., Bradley, A. and Zhang, X.X., (1991). Effect of ocular chromatic aberration on monocular visual performance. Optom. Vis. Sci., 68, 599-607.

Ekman P., Friesen WV. (1978b), Facial Action Coding System, Investigator’s Guide Part 2, Consulting Psychologists Press Inc.

MARTINEZ-CONDE, S, MACKNIK, S. AND HUBEL, D. 2004. The Role of Fixational Eye Movements in Visual Perception. Nature Reviews: Neuro- science, 5, March.

BARTEN, P. 1999. Contrast Sensitivity of the Human Eye and Its Effects on Image Quality. SPIE.

WYATT, H. 1995. The Form of the Human Pupil. Vision Research, 35, 14, 2021-2036.

DaugmanJ.Pheno typic versus geno typic approaches to face recognition. In: Face Recognition: From Theory to Applications. Heidelberg: Springer-Verlag, (1998), pp 108 -123.

George F. Luger. Artificial Intelligence: Structures and Strategies for Complex Problem Solving (Fifth Edition). Pearson Education, 2005.

Charles Darwin. Expression of the Emotions in Man and Animals. John Murray, London, United Kingdom, 1872.

Keith Waters. A muscle model for animation three-dimensional facial expression. SIGGRAPH Comput. Graph., 21(4):17–24, 1987.

BORSHUKOV, G., AND LEWIS, J. P. 2003. Realistic human face rendering for ’The Matrix Reloaded’. In ACM SIGGRAPH 2003 Sketches & Applications.

ICT-GRAPHICS-LABORATORY, 2001. Realistic human face scanning and rendering. Web site. http://gl.ict.usc.edu/Research/facescan/.

DEBEVEC, P. 1998. Rendering synthetic objects into real scenes: Bridging traditional and image-based graphics with global il- lumination and high dynamic range photography. In Proceed- ings of SIGGRAPH 98, Computer Graphics Proceedings, Annual Conference Series, 189–198.
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