Motion Capture History, Technologies and Applications

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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