{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T07:52:47Z","timestamp":1775289167956,"version":"3.50.1"},"reference-count":74,"publisher":"Association for Computing Machinery (ACM)","issue":"6","license":[{"start":{"date-parts":[[2018,12,4]],"date-time":"2018-12-04T00:00:00Z","timestamp":1543881600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-sa\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Graph."],"published-print":{"date-parts":[[2018,12,31]]},"abstract":"<jats:p>The advent of consumer depth cameras has incited the development of a new cohort of algorithms tackling challenging computer vision problems. The primary reason is that depth provides direct geometric information that is largely invariant to texture and illumination. As such, substantial progress has been made in human and object pose estimation, 3D reconstruction and simultaneous localization and mapping. Most of these algorithms naturally benefit from the ability to accurately track the pose of an object or scene of interest from one frame to the next. However, commercially available depth sensors (typically running at 30fps) can allow for large inter-frame motions to occur that make such tracking problematic. A high frame rate depth camera would thus greatly ameliorate these issues, and further increase the tractability of these computer vision problems. Nonetheless, the depth accuracy of recent systems for high-speed depth estimation [Fanello et al. 2017b] can degrade at high frame rates. This is because the active illumination employed produces a low SNR and thus a high exposure time is required to obtain a dense accurate depth image. Furthermore in the presence of rapid motion, longer exposure times produce artifacts due to motion blur, and necessitates a lower frame rate that introduces large inter-frame motion that often yield tracking failures. In contrast, this paper proposes a novel combination of hardware and software components that avoids the need to compromise between a dense accurate depth map and a high frame rate. We document the creation of a full 3D capture system for high speed and quality depth estimation, and demonstrate its advantages in a variety of tracking and reconstruction tasks. We extend the state of the art active stereo algorithm presented in Fanello et al. [2017b] by adding a space-time feature in the matching phase. We also propose a machine learning based depth refinement step that is an order of magnitude faster than traditional postprocessing methods. We quantitatively and qualitatively demonstrate the benefits of the proposed algorithms in the acquisition of geometry in motion. Our pipeline executes in 1.1ms leveraging modern GPUs and off-the-shelf cameras and illumination components. We show how the sensor can be employed in many different applications, from [non-]rigid reconstructions to hand\/face tracking. Further, we show many advantages over existing state of the art depth camera technologies beyond framerate, including latency, motion artifacts, multi-path errors, and multi-sensor interference.<\/jats:p>","DOI":"10.1145\/3272127.3275062","type":"journal-article","created":{"date-parts":[[2018,11,28]],"date-time":"2018-11-28T14:16:10Z","timestamp":1543414570000},"page":"1-14","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":26,"title":["The need 4 speed in real-time dense visual tracking"],"prefix":"10.1145","volume":"37","author":[{"given":"Adarsh","family":"Kowdle","sequence":"first","affiliation":[{"name":"Google Inc."}]},{"given":"Christoph","family":"Rhemann","sequence":"additional","affiliation":[{"name":"Google Inc."}]},{"given":"Sean","family":"Fanello","sequence":"additional","affiliation":[{"name":"Google Inc."}]},{"given":"Andrea","family":"Tagliasacchi","sequence":"additional","affiliation":[{"name":"Google Inc."}]},{"given":"Jonathan","family":"Taylor","sequence":"additional","affiliation":[{"name":"Google Inc."}]},{"given":"Philip","family":"Davidson","sequence":"additional","affiliation":[{"name":"Google Inc."}]},{"given":"Mingsong","family":"Dou","sequence":"additional","affiliation":[{"name":"Google Inc."}]},{"given":"Kaiwen","family":"Guo","sequence":"additional","affiliation":[{"name":"Google Inc."}]},{"given":"Cem","family":"Keskin","sequence":"additional","affiliation":[{"name":"Google Inc."}]},{"given":"Sameh","family":"Khamis","sequence":"additional","affiliation":[{"name":"Google Inc."}]},{"given":"David","family":"Kim","sequence":"additional","affiliation":[{"name":"Google Inc."}]},{"given":"Danhang","family":"Tang","sequence":"additional","affiliation":[{"name":"Google Inc."}]},{"given":"Vladimir","family":"Tankovich","sequence":"additional","affiliation":[{"name":"Google Inc."}]},{"given":"Julien","family":"Valentin","sequence":"additional","affiliation":[{"name":"Google Inc."}]},{"given":"Shahram","family":"Izadi","sequence":"additional","affiliation":[{"name":"Google Inc."}]}],"member":"320","published-online":{"date-parts":[[2018,12,4]]},"reference":[{"key":"e_1_2_2_1_1","doi-asserted-by":"crossref","unstructured":"A. Bhandari A. Kadambi R. Whyte C. Barsi M. Feigin A.A. Dorrington and R. Raskar. 2014. Resolving Multi-path Interference in Time-of-Flight Imaging via Modulation Frequency Diversity and Sparse Regularization. CoRR (2014). A. Bhandari A. Kadambi R. Whyte C. Barsi M. Feigin A.A. Dorrington and R. Raskar. 2014. Resolving Multi-path Interference in Time-of-Flight Imaging via Modulation Frequency Diversity and Sparse Regularization. CoRR (2014).","DOI":"10.1364\/OL.39.001705"},{"key":"e_1_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/311535.311556"},{"key":"e_1_2_2_3_1","doi-asserted-by":"crossref","unstructured":"M. Bleyer C. Rhemann and C. Rother. 2011. PatchMatch Stereo - Stereo Matching with Slanted Support Windows. In BMVC. M. Bleyer C. Rhemann and C. Rother. 2011. PatchMatch Stereo - Stereo Matching with Slanted Support Windows. In BMVC.","DOI":"10.5244\/C.25.14"},{"key":"e_1_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33715-4_34"},{"key":"e_1_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2207676.2208335"},{"key":"e_1_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/0262-8856(92)90066-C"},{"key":"e_1_2_2_7_1","doi-asserted-by":"crossref","unstructured":"C. Ciliberto S. R. Fanello L. Natale and G. Metta. 2012. A heteroscedastic approach to independent motion detection for actuated visual sensors. In IROS. C. Ciliberto S. R. Fanello L. Natale and G. Metta. 2012. A heteroscedastic approach to independent motion detection for actuated visual sensors. In IROS.","DOI":"10.1109\/IROS.2012.6385943"},{"key":"e_1_2_2_8_1","volume-title":"Wynn","author":"D'Asaro L. Arthur","year":"2016","unstructured":"L. Arthur D'Asaro , Jean-Francois Seurin , and James D . Wynn . 2016 . The VCSEL Advantage: Increased Power , Efficiency Bring New Applications . (2016). L. Arthur D'Asaro, Jean-Francois Seurin, and James D. Wynn. 2016. The VCSEL Advantage: Increased Power, Efficiency Bring New Applications. (2016)."},{"key":"e_1_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2005.37"},{"key":"e_1_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3130800.3130801"},{"key":"e_1_2_2_11_1","volume-title":"Adarsh Kowdle, Sergio Orts Escolano, Christoph Rhemann, David Kim, Jonathan Taylor, Pushmeet Kohli, Vladimir Tankovich, and Shahram Izadi.","author":"Dou Mingsong","year":"2016","unstructured":"Mingsong Dou , Sameh Khamis , Yury Degtyarev , Philip Davidson , Sean Ryan Fanello , Adarsh Kowdle, Sergio Orts Escolano, Christoph Rhemann, David Kim, Jonathan Taylor, Pushmeet Kohli, Vladimir Tankovich, and Shahram Izadi. 2016 . Fusion4D: Real-time Performance Capture of Challenging Scenes . (2016). Mingsong Dou, Sameh Khamis, Yury Degtyarev, Philip Davidson, Sean Ryan Fanello, Adarsh Kowdle, Sergio Orts Escolano, Christoph Rhemann, David Kim, Jonathan Taylor, Pushmeet Kohli, Vladimir Tankovich, and Shahram Izadi. 2016. Fusion4D: Real-time Performance Capture of Challenging Scenes. (2016)."},{"key":"e_1_2_2_12_1","doi-asserted-by":"crossref","unstructured":"S. R. Fanello I. Gori G. Metta and F. Odone. 2013a. Keep it simple and sparse: Real-time action recognition. JMLR (2013). S. R. Fanello I. Gori G. Metta and F. Odone. 2013a. Keep it simple and sparse: Real-time action recognition. JMLR (2013).","DOI":"10.1007\/978-3-642-38628-2_4"},{"key":"e_1_2_2_13_1","doi-asserted-by":"crossref","unstructured":"Sean Ryan Fanello Ilaria Gori Giorgio Metta and Francesca Odone. 2013b. One-Shot Learning for Real-Time Action Recognition. In IbPRIA. Sean Ryan Fanello Ilaria Gori Giorgio Metta and Francesca Odone. 2013b. One-Shot Learning for Real-Time Action Recognition. In IbPRIA.","DOI":"10.1007\/978-3-642-38628-2_4"},{"key":"e_1_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/HUMANOIDS.2014.7041491"},{"key":"e_1_2_2_15_1","volume-title":"Hyperdepth: Learning depth from structured light without matching. CVPR","author":"Fanello Sean Ryan","year":"2016","unstructured":"Sean Ryan Fanello , Christoph Rhemann , Vladimir Tankovich , A Kowdle , S Orts Escolano , D Kim , and S Izadi . 2016 . Hyperdepth: Learning depth from structured light without matching. CVPR (2016). Sean Ryan Fanello, Christoph Rhemann, Vladimir Tankovich, A Kowdle, S Orts Escolano, D Kim, and S Izadi. 2016. Hyperdepth: Learning depth from structured light without matching. CVPR (2016)."},{"key":"e_1_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.418"},{"key":"e_1_2_2_17_1","volume-title":"UltraStereo: Efficient Learning-based Matching for Active Stereo Systems. CVPR","author":"Fanello Sean Ryan","year":"2017","unstructured":"Sean Ryan Fanello , Julien Valentin , Christoph Rhemann , Adarsh Kowdle , Vladimir Tankovich , and Shahram Izadi . 2017b. UltraStereo: Efficient Learning-based Matching for Active Stereo Systems. CVPR ( 2017 ). Sean Ryan Fanello, Julien Valentin, Christoph Rhemann, Adarsh Kowdle, Vladimir Tankovich, and Shahram Izadi. 2017b. UltraStereo: Efficient Learning-based Matching for Active Stereo Systems. CVPR (2017)."},{"key":"e_1_2_2_18_1","volume-title":"SVO: Fast semi-direct monocular visual odometry. In ICRA.","author":"Forster Christian","year":"2014","unstructured":"Christian Forster , Matia Pizzoli , and Davide Scaramuzza . 2014 . SVO: Fast semi-direct monocular visual odometry. In ICRA. Christian Forster, Matia Pizzoli, and Davide Scaramuzza. 2014. SVO: Fast semi-direct monocular visual odometry. In ICRA."},{"key":"e_1_2_2_19_1","volume-title":"SRA: Fast Removal of General Multipath for ToF Sensors. ECCV","author":"Freedman D.","year":"2014","unstructured":"D. Freedman , E. Krupka , Y. Smolin , I. Leichter , and M. Schmidt . 2014 . SRA: Fast Removal of General Multipath for ToF Sensors. ECCV (2014). D. Freedman, E. Krupka, Y. Smolin, I. Leichter, and M. Schmidt. 2014. SRA: Fast Removal of General Multipath for ToF Sensors. ECCV (2014)."},{"key":"e_1_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1364\/AOP.3.000128"},{"key":"e_1_2_2_21_1","volume-title":"Ultrafast 3-D shape measurement with an off-the-shelf DLP projector. Optics express","author":"Gong Yuanzheng","year":"2010","unstructured":"Yuanzheng Gong and Song Zhang . 2010. Ultrafast 3-D shape measurement with an off-the-shelf DLP projector. Optics express ( 2010 ). Yuanzheng Gong and Song Zhang. 2010. Ultrafast 3-D shape measurement with an off-the-shelf DLP projector. Optics express (2010)."},{"key":"e_1_2_2_22_1","volume-title":"Good Points: A Comprehensive Method for Humanoid Robots to Grasp Unknown Objects","author":"Gori I.","year":"2013","unstructured":"I. Gori , U. Pattacini , V. Tikhanoff , and G. Metta . 2013 . Ranking the Good Points: A Comprehensive Method for Humanoid Robots to Grasp Unknown Objects . In IEEE ICAR. I. Gori, U. Pattacini, V. Tikhanoff, and G. Metta. 2013. Ranking the Good Points: A Comprehensive Method for Humanoid Robots to Grasp Unknown Objects. In IEEE ICAR."},{"key":"e_1_2_2_23_1","doi-asserted-by":"crossref","unstructured":"Kaiwen Guo Jonathan Taylor Sean Fanello Andrea Tagliasacchi Mingsong Dou Philip Davidson Adarsh Kowdle and Shahram Izadi. 2018. TwinFusion: High Framerate Non-Rigid Fusion through Fast Correspondence Tracking. In 3DV. Kaiwen Guo Jonathan Taylor Sean Fanello Andrea Tagliasacchi Mingsong Dou Philip Davidson Adarsh Kowdle and Shahram Izadi. 2018. TwinFusion: High Framerate Non-Rigid Fusion through Fast Correspondence Tracking. In 3DV.","DOI":"10.1109\/3DV.2018.00074"},{"key":"e_1_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/2735702"},{"key":"e_1_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33786-4_17"},{"key":"e_1_2_2_27_1","volume-title":"Characteristics of digital micromirror projection for 3D shape measurement at extreme speed","author":"H\u00f6fling Roland","unstructured":"Roland H\u00f6fling , Petra Aswendt , Frank Leischnig , and Matthias F\u00f6rster . 2015. Characteristics of digital micromirror projection for 3D shape measurement at extreme speed . In SPIE OPTO. International Society for Optics and Photonics . Roland H\u00f6fling, Petra Aswendt, Frank Leischnig, and Matthias F\u00f6rster. 2015. Characteristics of digital micromirror projection for 3D shape measurement at extreme speed. In SPIE OPTO. International Society for Optics and Photonics."},{"key":"e_1_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(81)90024-2"},{"key":"e_1_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.156"},{"key":"e_1_2_2_30_1","volume-title":"High-speed high-accuracy three-dimensional shape measurement using digital binary defocusing method versus sinusoidal method. Optical Engineering","author":"Hyun Jae-Sang","year":"2017","unstructured":"Jae-Sang Hyun , Beiwen Li , and Song Zhang . 2017. High-speed high-accuracy three-dimensional shape measurement using digital binary defocusing method versus sinusoidal method. Optical Engineering ( 2017 ). Jae-Sang Hyun, Beiwen Li, and Song Zhang. 2017. High-speed high-accuracy three-dimensional shape measurement using digital binary defocusing method versus sinusoidal method. Optical Engineering (2017)."},{"key":"e_1_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46484-8_22"},{"key":"e_1_2_2_32_1","doi-asserted-by":"crossref","unstructured":"S. Izadi D. Kim O. Hilliges D. Molyneaux R. Newcombe P. Kohli J. Shotton S. Hodges D. Freeman A. Davison and A. Fitzgibbon. 2011. KinectFusion: Real-time 3D reconstruction and interaction using a moving depth camera. S. Izadi D. Kim O. Hilliges D. Molyneaux R. Newcombe P. Kohli J. Shotton S. Hodges D. Freeman A. Davison and A. Fitzgibbon. 2011. KinectFusion: Real-time 3D reconstruction and interaction using a moving depth camera.","DOI":"10.1145\/2037826.2037857"},{"key":"e_1_2_2_33_1","doi-asserted-by":"crossref","unstructured":"D. Jimenez D. Pizarro M. Mazo and S. Palazuelos. 2012. Modelling and correction of multipath interference in time of flight cameras. In CVPR. D. Jimenez D. Pizarro M. Mazo and S. Palazuelos. 2012. Modelling and correction of multipath interference in time of flight cameras. In CVPR.","DOI":"10.1109\/CVPR.2012.6247763"},{"key":"e_1_2_2_34_1","volume-title":"Intel RealSense Stereoscopic Depth Cameras. CVPR Workshops","author":"Keselman L.","year":"2017","unstructured":"L. Keselman , J. Iselin Woodfill , A. Grunnet-Jepsen , and A. Bhowmik . 2017 . Intel RealSense Stereoscopic Depth Cameras. CVPR Workshops ( 2017 ). L. Keselman, J. Iselin Woodfill, A. Grunnet-Jepsen, and A. Bhowmik. 2017. Intel RealSense Stereoscopic Depth Cameras. CVPR Workshops (2017)."},{"key":"e_1_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33783-3_61"},{"key":"e_1_2_2_36_1","volume-title":"Christoph Rhemann, Julien Valentin, Adarsh Kowdle, and Shahram Izadi.","author":"Khamis Sameh","year":"2018","unstructured":"Sameh Khamis , Sean Ryan Fanello , Christoph Rhemann, Julien Valentin, Adarsh Kowdle, and Shahram Izadi. 2018 . StereoNet: Guided Hierarchical Refinement for Real-Time Edge-Aware Depth Prediction . ECCV (2018). Sameh Khamis, Sean Ryan Fanello, Christoph Rhemann, Julien Valentin, Adarsh Kowdle, and Shahram Izadi. 2018. StereoNet: Guided Hierarchical Refinement for Real-Time Edge-Aware Depth Prediction. ECCV (2018)."},{"key":"e_1_2_2_37_1","volume-title":"Need for Speed: A Benchmark for Higher Frame Rate Object Tracking. In The IEEE International Conference on Computer Vision (ICCV).","author":"Galoogahi Hamed Kiani","year":"2017","unstructured":"Hamed Kiani Galoogahi , Ashton Fagg , Chen Huang , Deva Ramanan , and Simon Lucey . 2017 . Need for Speed: A Benchmark for Higher Frame Rate Object Tracking. In The IEEE International Conference on Computer Vision (ICCV). Hamed Kiani Galoogahi, Ashton Fagg, Chen Huang, Deva Ramanan, and Simon Lucey. 2017. Need for Speed: A Benchmark for Higher Frame Rate Object Tracking. In The IEEE International Conference on Computer Vision (ICCV)."},{"key":"e_1_2_2_38_1","volume-title":"Davison","author":"Kim Hanme","year":"2016","unstructured":"Hanme Kim , Stefan Leutenegger , and Andrew J . Davison . 2016 . Real-Time 3D Reconstruction and 6-DoF Tracking with an Event Camera . Hanme Kim, Stefan Leutenegger, and Andrew J. Davison. 2016. Real-Time 3D Reconstruction and 6-DoF Tracking with an Event Camera."},{"key":"e_1_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1111\/cgf.12573"},{"key":"e_1_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3025453.3025478"},{"key":"e_1_2_2_41_1","volume-title":"Proc","author":"Moench Holger","unstructured":"Holger Moench , Mark Carpaij , Philipp Gerlach , Stephan Gronenborn , Ralph Gudde , Jochen Hellmig , Johanna Kolb , and Alexander van der Lee . 2016. VCSEL-based sensors for distance and velocity . In Proc . International Society for Optics and Photonics . Holger Moench, Mark Carpaij, Philipp Gerlach, Stephan Gronenborn, Ralph Gudde, Jochen Hellmig, Johanna Kolb, and Alexander van der Lee. 2016. VCSEL-based sensors for distance and velocity. In Proc. International Society for Optics and Photonics."},{"key":"e_1_2_2_42_1","doi-asserted-by":"crossref","unstructured":"N. Naik A. Kadambi C. Rhemann S. Izadi R. Raskar and S.B. Kang. 2015. A Light Transport Model for Mitigating Multipath Interference in TOF Sensors. CVPR (2015). N. Naik A. Kadambi C. Rhemann S. Izadi R. Raskar and S.B. Kang. 2015. A Light Transport Model for Mitigating Multipath Interference in TOF Sensors. CVPR (2015).","DOI":"10.1109\/CVPR.2015.7298602"},{"key":"e_1_2_2_43_1","doi-asserted-by":"crossref","unstructured":"Yoshihiro Nakabo Masatoshi Ishikawa Haruyoshi Toyoda and Seiichiro Mizuno. 2000. 1ms Column Parallel Vision System and Its Application of High Speed Target Tracking. In ICRA. Yoshihiro Nakabo Masatoshi Ishikawa Haruyoshi Toyoda and Seiichiro Mizuno. 2000. 1ms Column Parallel Vision System and Its Application of High Speed Target Tracking. In ICRA.","DOI":"10.1109\/ROBOT.2000.844126"},{"key":"e_1_2_2_45_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISMAR.2011.6092378"},{"key":"e_1_2_2_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2011.5980080"},{"key":"e_1_2_2_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/2984511.2984517"},{"key":"e_1_2_2_48_1","unstructured":"OSHA. 2017. OSHA Technical Manual (OTM) by United States. Occupational Safety and Health Administration. Office of Science and Technology Assessment. OSHA. 2017. OSHA Technical Manual (OTM) by United States. Occupational Safety and Health Administration. Office of Science and Technology Assessment."},{"key":"e_1_2_2_49_1","doi-asserted-by":"publisher","DOI":"10.1145\/2601097.2601103"},{"key":"e_1_2_2_50_1","doi-asserted-by":"publisher","DOI":"10.1109\/VR.2017.7892280"},{"key":"e_1_2_2_51_1","doi-asserted-by":"crossref","unstructured":"V. Pradeep C. Rhemann S.i Izad C. Zach M. Bleyer and S. Bathiche. 2013. MonoFusion: Real-time 3D Reconstruction of Small Scenes with a Single Web Camera. V. Pradeep C. Rhemann S.i Izad C. Zach M. Bleyer and S. Bathiche. 2013. MonoFusion: Real-time 3D Reconstruction of Small Scenes with a Single Web Camera.","DOI":"10.1109\/ISMAR.2013.6671767"},{"key":"e_1_2_2_52_1","volume-title":"EVO: A Geometric Approach to Event-Based 6-DOF Parallel Tracking and Mapping in Real Time","author":"Rebecq H.","year":"2017","unstructured":"H. Rebecq , T. Horstschaefer , G. Gallego , and D. Scaramuzza . 2017 . EVO: A Geometric Approach to Event-Based 6-DOF Parallel Tracking and Mapping in Real Time . IEEE Robotics and Automation Letters ( 2017). H. Rebecq, T. Horstschaefer, G. Gallego, and D. Scaramuzza. 2017. EVO: A Geometric Approach to Event-Based 6-DOF Parallel Tracking and Mapping in Real Time. IEEE Robotics and Automation Letters (2017)."},{"key":"e_1_2_2_53_1","volume-title":"Real-Time Panoramic Tracking for Event Cameras. arXiv preprint arXiv:1703.05161","author":"Reinbacher Christian","year":"2017","unstructured":"Christian Reinbacher , Gottfried Munda , and Thomas Pock . 2017. Real-Time Panoramic Tracking for Event Cameras. arXiv preprint arXiv:1703.05161 ( 2017 ). Christian Reinbacher, Gottfried Munda, and Thomas Pock. 2017. Real-Time Panoramic Tracking for Event Cameras. arXiv preprint arXiv:1703.05161 (2017)."},{"key":"e_1_2_2_54_1","unstructured":"RoadToVR. 2016. Analysis of Valve's 'Lighthouse' Tracking System Reveals Accuracy. http:\/\/www.roadtovr.com\/analysis-of-valves-lighthouse-tracking-system-reveals-accuracy\/. (2016). RoadToVR. 2016. Analysis of Valve's 'Lighthouse' Tracking System Reveals Accuracy. http:\/\/www.roadtovr.com\/analysis-of-valves-lighthouse-tracking-system-reveals-accuracy\/. (2016)."},{"key":"e_1_2_2_55_1","doi-asserted-by":"crossref","unstructured":"Jannick P. Rolland Richard L. Holloway and Henry Fuchs. 1995. Comparison of optical and video see-through head-mounted displays. (1995). Jannick P. Rolland Richard L. Holloway and Henry Fuchs. 1995. Comparison of optical and video see-through head-mounted displays. (1995).","DOI":"10.1117\/12.197322"},{"key":"e_1_2_2_56_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2010.03.004"},{"key":"e_1_2_2_57_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1014573219977"},{"key":"e_1_2_2_58_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995316"},{"key":"e_1_2_2_59_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.377"},{"key":"e_1_2_2_60_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298941"},{"key":"e_1_2_2_61_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.408"},{"key":"e_1_2_2_62_1","doi-asserted-by":"publisher","DOI":"10.1145\/1276377.1276478"},{"key":"e_1_2_2_63_1","unstructured":"A. Takgi S. Yamazaki and H. Fuchs. 2000. Development of a stereo video see-through HMD for AR systems. (2000). A. Takgi S. Yamazaki and H. Fuchs. 2000. Development of a stereo video see-through HMD for AR systems. (2000)."},{"key":"e_1_2_2_64_1","doi-asserted-by":"publisher","DOI":"10.1145\/2897824.2925965"},{"key":"e_1_2_2_65_1","doi-asserted-by":"publisher","DOI":"10.1145\/3130800.3130853"},{"key":"e_1_2_2_66_1","doi-asserted-by":"publisher","DOI":"10.1145\/3084822.3084841"},{"key":"e_1_2_2_67_1","doi-asserted-by":"publisher","DOI":"10.1145\/2980179.2980226"},{"key":"e_1_2_2_68_1","unstructured":"R. Y. Tsai and R. K. Lenz. 1988. Real time versatile robotics hand\/eye calibration using 3D machine vision. In ICRA. R. Y. Tsai and R. K. Lenz. 1988. Real time versatile robotics hand\/eye calibration using 3D machine vision. In ICRA."},{"key":"e_1_2_2_69_1","doi-asserted-by":"publisher","DOI":"10.1145\/2751556"},{"key":"e_1_2_2_70_1","volume-title":"Christoph Rhemann, Shahram Izadi, and Pushmeet Kohli.","author":"Wang Shenlong","year":"2016","unstructured":"Shenlong Wang , Sean Ryan Fanello , Christoph Rhemann, Shahram Izadi, and Pushmeet Kohli. 2016 . The Global Patch Collider. CVPR ( 2016). Shenlong Wang, Sean Ryan Fanello, Christoph Rhemann, Shahram Izadi, and Pushmeet Kohli. 2016. The Global Patch Collider. CVPR (2016)."},{"key":"e_1_2_2_71_1","volume-title":"Haptics Symposium (HAPTICS)","author":"Webster D.","year":"2014","unstructured":"D. Webster and O. Celik . 2014. Experimental evaluation of Microsoft Kinect's accuracy and capture rate for stroke rehabilitation applications . In Haptics Symposium (HAPTICS) , 2014 IEEE. IEEE, 455--460. D. Webster and O. Celik. 2014. Experimental evaluation of Microsoft Kinect's accuracy and capture rate for stroke rehabilitation applications. In Haptics Symposium (HAPTICS), 2014 IEEE. IEEE, 455--460."},{"key":"e_1_2_2_72_1","volume-title":"Spacetime Stereo: Shape Recovery for Dynamic Scenes. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 367--374","author":"Zhang Li","unstructured":"Li Zhang , Brian Curless , and Steven M. Seitz . 2003 . Spacetime Stereo: Shape Recovery for Dynamic Scenes. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 367--374 . Li Zhang, Brian Curless, and Steven M. Seitz. 2003. Spacetime Stereo: Shape Recovery for Dynamic Scenes. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 367--374."},{"key":"e_1_2_2_73_1","volume-title":"Daniel Van Der Weide, and James Oliver","author":"Zhang Song","year":"2010","unstructured":"Song Zhang , Daniel Van Der Weide, and James Oliver . 2010 . Superfast phase-shifting method for 3-D shape measurement. Optics express (2010). Song Zhang, Daniel Van Der Weide, and James Oliver. 2010. Superfast phase-shifting method for 3-D shape measurement. Optics express (2010)."},{"key":"e_1_2_2_74_1","volume-title":"ActiveStereoNet: End-to-End Self-Supervised Learning for Active Stereo Systems. ECCV","author":"Zhang Yinda","year":"2018","unstructured":"Yinda Zhang , Sameh Khamis , Christoph Rhemann , Julien Valentin , Adarsh Kowdle , Vladimir Tankovich , Michael Schoenberg , Shahram Izadi , Thomas Funkhouser , and Sean Fanello . 2018. ActiveStereoNet: End-to-End Self-Supervised Learning for Active Stereo Systems. ECCV ( 2018 ). Yinda Zhang, Sameh Khamis, Christoph Rhemann, Julien Valentin, Adarsh Kowdle, Vladimir Tankovich, Michael Schoenberg, Shahram Izadi, Thomas Funkhouser, and Sean Fanello. 2018. ActiveStereoNet: End-to-End Self-Supervised Learning for Active Stereo Systems. ECCV (2018)."},{"key":"e_1_2_2_75_1","doi-asserted-by":"publisher","DOI":"10.1145\/2601097.2601165"},{"key":"e_1_2_2_76_1","volume-title":"High-speed three-dimensional shape measurement for dynamic scenes using bi-frequency tripolar pulse-width-modulation fringe projection. Optics and Lasers in Engineering","author":"Zuo Chao","year":"2013","unstructured":"Chao Zuo , Qian Chen , Guohua Gu , Shijie Feng , Fangxiaoyu Feng , Rubin Li , and Guochen Shen . 2013. High-speed three-dimensional shape measurement for dynamic scenes using bi-frequency tripolar pulse-width-modulation fringe projection. Optics and Lasers in Engineering ( 2013 ). Chao Zuo, Qian Chen, Guohua Gu, Shijie Feng, Fangxiaoyu Feng, Rubin Li, and Guochen Shen. 2013. High-speed three-dimensional shape measurement for dynamic scenes using bi-frequency tripolar pulse-width-modulation fringe projection. Optics and Lasers in Engineering (2013)."}],"container-title":["ACM Transactions on Graphics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3272127.3275062","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3272127.3275062","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T06:59:04Z","timestamp":1775285944000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3272127.3275062"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,12,4]]},"references-count":74,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2018,12,31]]}},"alternative-id":["10.1145\/3272127.3275062"],"URL":"https:\/\/doi.org\/10.1145\/3272127.3275062","relation":{},"ISSN":["0730-0301","1557-7368"],"issn-type":[{"value":"0730-0301","type":"print"},{"value":"1557-7368","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,12,4]]},"assertion":[{"value":"2018-12-04","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}