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Motion Capture History, Technologies and Applications Motion Capture History, Technologies and Applications Advanced Computing Center for the Arts and Design Ohio State University Vita Berezina-Blackburn ©2003- 2016, The Ohio State University Motion Capture • motion capture (mocap) is sampling and recording motion of humans, animals and inanimate objects as 3d data for analysis, playback and remapping • performance capture is acting with motion capture in film and games • motion tracking is real-time processing of motion capture data ©2003- 2016, The Ohio State University History of Motion Capture • Eadweard Muybridge (1830-1904) • Etienne-Jules Marey (1830-1904) • Nikolai Bernstein (1896-1966) • Harold Edgerton (1903-1990) • Gunnar Johansson (1911- 1998) ©2003- 2016, The Ohio State University Eadward Muybridge • the flying horse • 20,000 photos of animal and human locomotion • UK-USA, 1872 © Kingston Museum ©2003- 2016, The Ohio State University Eadward Muybridge • zoopraxiscope © Kingston Museum ©2003- 2016, The Ohio State University Etienne-Jules Marey • first person to analyze human and animal motion with film • created chronophotographic gun and fixed plate camera • France, 1880s ©2003- 2016, The Ohio State University Modern Art • Futurism (Boccionni, Balla and others) • Marcel Duchamp ©2003- 2016, The Ohio State University Rotoscoping • allowed animators to trace cartoon characters over photographed frames of live performances. • invented in 1915 by Max Fleischer • Koko the Clown • Snow White © Walt Disney ©2003- 2016, The Ohio State University Nikolai Bernstein • General Biomechanics – 1924, Central Institute of Labor, Moscow • physiology of sport and labor activities, foundations of ergonomics • cyclography • concepts of degrees of freedom and hierarchical structure of motion control ©2003- 2016, The Ohio State University Harold Edgerton • electronic stroboscope and flash • exposures of 1/1000th to 1/1000000 sec • MIT, 1930s-1960 © Palm Press Inc. ©2003- 2016, The Ohio State University GUNNAR JOHANSSON • Visual perception of biological motion, experimental psychology, 1970s, University of Uppsala, Sweden • Retro-reflective patches on joints • Video recording instead of film, search light mounted very closely to the camera lens, light reflects from patches into the lens • Computer modeling of motion variations ©2003- 2016, The Ohio State University 1980’s Computer Graphics • military and medical research purposes • first computer graphics use in research labs • first production use o Brilliance by Robert Abel , brute force animation technique(1985 Superbowl ad) o Waldo C. Graphic (1988) PDI for Jim Henson tour o Mike the Talking Head (Siggraph 88) ’ o Don t Touch Me (1989) ©2003- 2016, The Ohio State University Mocap Technologies ACTIVE PASSIVE •electromechanical •optical: retroreflective markers •optical fiber •acoustic •optical: strobing LEDs •optical markerless (video based) •acoustic •inertial •optical markerless based on structured light •optical markerless based on video ©2003- 2016, The Ohio State University Optical motion capture systems • light weight, variable size, retro- reflective markers • VGA to16 megapixel resolution cameras with strobing LEDs digitize different views of performance • up to 5000fps • under 1mm accuracy • marker occlusion • capture volume limits VICON NATURAL POINT MOTION ANALYSIS QUALISYS ©2003- 2016, The Ohio State University Strobing LED marker system • red or Infrared LEDs • unique strobing frequency for each marker • no marker swapping • limited volume • limited capture time due to battery life for LED • wires running up and down capture subject PHASESPACE ©2003- 2016, The Ohio State University Electromechanical suits • linked structures • potentiometers determine degree of rotation for each link • no occlusion • no magnetic or electrical interference • unlimited capture volume • low cost • no global translation • restricted movement • fixed configuration of sensors • low sampling rate • inaccurate joints GYPSY MOCAP SYSTEM ©2003- 2016, The Ohio State University Inertial systems • inertial trackers placed on joints • measures orientation and position with accelerometers, gyroscopes, magnetometers on each segment • UWB RF for position tracking • unlimited capture volume • no occlusion, multiple subjects • positional drift • translational data needs to be collected separately • battery packs and wires on the performer’s body. XSENS MOCAP SYSTEM ©2003- 2016, The Ohio State University Electromagnetic systems • electromagnetic sensors placed on joints or other critical points • measures orientation and position of sensor relative to electromagnetic field generated by the transmitter • no sight line requirements • no occlusion, multiple subjects • electromagnetic interference, small volume if body translation tracking is needed ASCENSION-TECH NORTHERN DIGITAL ©2003- 2016, The Ohio State University Optical fiber system • fiber-optic sensor • bend and twist sensors measure transmitted light • no occlusion • flexible capture volume • adjustment to individual proportions is limited • less accurate data CYBERGLOVE ©2003- 2016, The Ohio State University Acoustic system • set of transducers/transcievers generate and evaluate high frequency sound wave • other sounds in frequency range can disrupt capture • accuracy not as high as other systems INTERSENSE ©2003- 2016, The Ohio State University Markerless Motion Capture Full Body o Max Plank Institute research (3d scanner + silhouette analysis from video) o Captury ©2003- 2016, The Ohio State University Markerless Motion Capture Full Body o Kinect and other RGB-d sensor development ORGANIC MOTION ILM and ManhattanMocap Group’s Multitrack System (markers for computer vision) ©2003- 2016, The Ohio State University Markerless Motion Capture Face FACS/Paul Ekman Video based: Original R&D: Digital Emily Project Faceware Medusa (Disney Zurich) RGB-d based: Faceshift ©2003- 2016, The Ohio State University Markerless Motion Capture Hands Leap Sensor ©2003- 2016, The Ohio State University Video-based Motion Analysis Research Areas o equipment and subject calibration o motion tracking o 3D movement reconstruction (markerless motion capture) o skeletal solving o action recognition o 3D surface reconstruction (surface scanning) Challenges: o complex environment variability o body segmentation o occlusion o data volume ©2003- 2016, The Ohio State University Typical Marker Based Optical Motion Capture Pipeline • planning (performers and actions, props, space requirements) • recording point data(Vicon Blade) • data processing, realtime or post standard skeletal solving (Vicon Blade, MotionBuilder, Ikinema ) • skeleton creation (3d animation software) • remapping standard skeletal motion to customized characters (MotionBuilder) • binding skeleton to a model (3D animation software) ©2003- 2016, The Ohio State University Optical Marker Based 3D Motion Reconstruction • Single camera o Model assumptions required • Multiple cameras o Require at least 2 cameras, unique with 3 o Camera calibration • Motion capture with markers o Use retroreflective markers to simplify video information ©2003- 2016, The Ohio State University Problems Related to Marker Occlusion ©2003- 2016, The Ohio State University Skeletal Solving (remapping mocap data to a character model) • how to make markers move a skeleton o photo reference or 3d scan of a performer o CG model o Motion Builder or Ikinema o Vicon Blade o other methods • problems with detecting joint centers… • organization of joint hierarchies ©2003- 2016, The Ohio State University Planning • shot list • performance space dimensions • interactions in shot • shots to be blended or looped • length of shots • size and location of props • gross proportional differences for retargeting • camera motion ©2003- 2016, The Ohio State University Planning • Character/Prop setup o target skeleton/character topology o ready stance considerations o space preparation/occlusion removal/ camera stability • Marker setup o marker redundancy o three markers per segment o place markers close to bone o asymmetry o recognizable configuration • output format • file naming conventions • frame rate • target software platform • database management • potential technical issues ©2003- 2016, The Ohio State University Virtual Production • Pioneered for the production of James Cameron’s “Avatar” • virtual camera • simulcam ©2003- 2016, The Ohio State University Feature Films, Games and VR applications • Avatar • Dawn of the Planet of the Apes • The Force Awakens • Curious Case of Benjamin Button • EA Sports football capture session • EA Sports soccer capture session • ILMxLab • PrioVR • Sixense • VR news ©2003- 2016, The Ohio State University Applications • Biomedical and Physical Rehabilitation Mixed Reality Rehabilitation Markerless Gait Analysis Tongue Capture for Speech Therapy ©2003- 2016, The Ohio State University Applications • Historical Preservation Native American Performance • Arts Open Ended Group Walking City ACCAD Motion Lab Deakin University Motion Lab Projects Virtual Puppets in Landing Place Robotic Camera Choreography via Motion Capture ©2003- 2016, The Ohio State University Applications • Life Sciences • Engineering • Military and Law Enforcement VR weapon training with acoustic tracking system Virtual Crime Scene Simulation • Sports Golf Training Simulator Various Sports Analysis and Training ©2003- 2016, The Ohio State University Motion Technology and Integration Researchers • Univesity of South California (Paul Debevec) • Chris Bregler (NYU, Stanford, Google) • Carnegie Mellon (Jessica Hodgins)
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