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2014 | OriginalPaper | Buchkapitel

2. A State of the Art Report on Multiple RGB-D Sensor Research and on Publicly Available RGB-D Datasets

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Abstract

That the Microsoft Kinect, an RGB-D sensor, transformed the gaming and end consumer sector has been anticipated by the developers. That it also impacted in rigorous computer vision research has probably been a surprise to the whole community. Shortly before the commercial deployment of its successor, Kinect One, the research literature fills with resumees and state-of-the art papers to summarize the development over the past 3 years. This chapter describes significant research projects which have built on sensoring setups that include two or more RGB-D sensors in one scene and on RGB-D datasets captured with them which were made publicly available.

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Literatur
1.
Zurück zum Zitat Ahmed N (2012) A system for 360 acquisition and 3D animation reconstruction using multiple RGB-D cameras Ahmed N (2012) A system for 360 acquisition and 3D animation reconstruction using multiple RGB-D cameras
2.
Zurück zum Zitat Alexiadis DS, Kordelas G, Apostolakis KC, Agapito JD, Vegas J, Izquierdo E, Daras P (2012) Reconstruction for 3D immersive virtual environments. In: 13th international workshop on image analysis for multimedia interactive services (WIAMIS). IEEE, pp 1–4 Alexiadis DS, Kordelas G, Apostolakis KC, Agapito JD, Vegas J, Izquierdo E, Daras P (2012) Reconstruction for 3D immersive virtual environments. In: 13th international workshop on image analysis for multimedia interactive services (WIAMIS). IEEE, pp 1–4
3.
Zurück zum Zitat Anand A, Koppula HS, Joachims T, Saxena A (2013) Contextually guided semantic labeling and search for three-dimensional point clouds. Int J Robot Res 32(1):19–34CrossRef Anand A, Koppula HS, Joachims T, Saxena A (2013) Contextually guided semantic labeling and search for three-dimensional point clouds. Int J Robot Res 32(1):19–34CrossRef
4.
Zurück zum Zitat Asteriadis S, Chatzitofis A, Zarpalas D, Alexiadis DS, Daras P (2013) Estimating human motion from multiple kinect sensors. In: Proceedings of the 6th international conference on computer vision/computer graphics collaboration techniques and applications. ACM, p 3 Asteriadis S, Chatzitofis A, Zarpalas D, Alexiadis DS, Daras P (2013) Estimating human motion from multiple kinect sensors. In: Proceedings of the 6th international conference on computer vision/computer graphics collaboration techniques and applications. ACM, p 3
5.
Zurück zum Zitat Barbosa IB, Cristani M, Del Bue A, Bazzani L, Murino V (2012) Re-identification with RGB-D sensors. In: Computer vision-ECCV 2012. Workshops and demonstrations. Springer, pp 433–442 Barbosa IB, Cristani M, Del Bue A, Bazzani L, Murino V (2012) Re-identification with RGB-D sensors. In: Computer vision-ECCV 2012. Workshops and demonstrations. Springer, pp 433–442
6.
Zurück zum Zitat Berger K, Kastner M, Schroeder Y, Guthe S (2013) Using sparse optical flow for two-phase gas flow capturing with multiple kinects. Robotics: science and systems 2013 workshop on RGB-D: advanced reasoning with depth cameras, pp 1–8 Berger K, Kastner M, Schroeder Y, Guthe S (2013) Using sparse optical flow for two-phase gas flow capturing with multiple kinects. Robotics: science and systems 2013 workshop on RGB-D: advanced reasoning with depth cameras, pp 1–8
7.
Zurück zum Zitat Berger K, Ruhl K, Albers M, Schroder Y, Scholz A, Kokemuller J, Guthe S, Magnor M (2011) The capturing of turbulent gas flows using multiple kinects. In: IEEE international conference on computer vision workshops (ICCV workshops). IEEE, pp 1108–1113 Berger K, Ruhl K, Albers M, Schroder Y, Scholz A, Kokemuller J, Guthe S, Magnor M (2011) The capturing of turbulent gas flows using multiple kinects. In: IEEE international conference on computer vision workshops (ICCV workshops). IEEE, pp 1108–1113
8.
Zurück zum Zitat Berger K, Ruhl K, Brümmer C, Schröder Y, Scholz A, Magnor M (2011) Markerless motion capture using multiple color-depth sensors. In Proceedings of vision, modeling and visualization (VMV), vol 2011, p 3 Berger K, Ruhl K, Brümmer C, Schröder Y, Scholz A, Magnor M (2011) Markerless motion capture using multiple color-depth sensors. In Proceedings of vision, modeling and visualization (VMV), vol 2011, p 3
9.
Zurück zum Zitat Butler DA, Izadi S, Hilliges O, Molyneaux D, Hodges S, Kim D (2012) Shake‘n’sense: reducing interference for overlapping structured light depth cameras. In: Proceedings of the 2012 ACM annual conference on human factors in computing systems. ACM, pp 1933–1936 Butler DA, Izadi S, Hilliges O, Molyneaux D, Hodges S, Kim D (2012) Shake‘n’sense: reducing interference for overlapping structured light depth cameras. In: Proceedings of the 2012 ACM annual conference on human factors in computing systems. ACM, pp 1933–1936
10.
Zurück zum Zitat Caon M, Yue Y, Tscherrig J, Mugellini E, Abou Khaled O (2011) Context-aware 3D gesture interaction based on multiple kinects. In: AMBIENT 2011, the first international conference on ambient computing, applications, services and technologies, pp 7–12 Caon M, Yue Y, Tscherrig J, Mugellini E, Abou Khaled O (2011) Context-aware 3D gesture interaction based on multiple kinects. In: AMBIENT 2011, the first international conference on ambient computing, applications, services and technologies, pp 7–12
11.
Zurück zum Zitat Faion F, Friedberger S, Zea A, Hanebeck UD (2012) Intelligent sensor-scheduling for multi-kinect-tracking. In: IEEE/RSJ international conference on intelligent robots and systems (IROS). IEEE, pp 3993–3999 Faion F, Friedberger S, Zea A, Hanebeck UD (2012) Intelligent sensor-scheduling for multi-kinect-tracking. In: IEEE/RSJ international conference on intelligent robots and systems (IROS). IEEE, pp 3993–3999
12.
Zurück zum Zitat Fuhrmann AL, Kretz J, Burwik P (2013) Multi sensor tracking for live sound transformation Fuhrmann AL, Kretz J, Burwik P (2013) Multi sensor tracking for live sound transformation
13.
Zurück zum Zitat Glocker B, Izadi S, Shotton J, Criminisi A (2013) Real-time RGB-D camera relocalization. In: International symposium on mixed and augmented reality. Springer Glocker B, Izadi S, Shotton J, Criminisi A (2013) Real-time RGB-D camera relocalization. In: International symposium on mixed and augmented reality. Springer
14.
Zurück zum Zitat Han J, Shao L, Xu D, Shotton J (2013) Enhanced computer vision with microsoft kinect sensor: a review Han J, Shao L, Xu D, Shotton J (2013) Enhanced computer vision with microsoft kinect sensor: a review
15.
Zurück zum Zitat Hossny M, Filippidis D, Abdelrahman W, Zhou H, Fielding M, Mullins J, Wei L, Creighton D, Puri V, Nahavandi S (2012) Low cost multimodal facial recognition via kinect sensors. In: Proceedings of the land warfare conference (LWC): potent land force for a joint maritime strategy. Commonwealth of Australia, pp 77–86 Hossny M, Filippidis D, Abdelrahman W, Zhou H, Fielding M, Mullins J, Wei L, Creighton D, Puri V, Nahavandi S (2012) Low cost multimodal facial recognition via kinect sensors. In: Proceedings of the land warfare conference (LWC): potent land force for a joint maritime strategy. Commonwealth of Australia, pp 77–86
16.
Zurück zum Zitat Huynh T, Min R, Dugelay J-L (2013) An efficient LBP-based descriptor for facial depth images applied to gender recognition using RGB-D face data. In: Computer vision-ACCV 2012 workshops. Springer, pp 133–145 Huynh T, Min R, Dugelay J-L (2013) An efficient LBP-based descriptor for facial depth images applied to gender recognition using RGB-D face data. In: Computer vision-ACCV 2012 workshops. Springer, pp 133–145
17.
Zurück zum Zitat Izadi S, Newcombe R, Kim D, Hilliges O, Molyneaux D, Hodges S, Kohli P, Shotton J, Davison A, Fitzgibbon A (2011) Kinectfusion: real-time dynamic 3D surface reconstruction and interaction. In: ACM SIGGRAPH 2011 talks. ACM, p 23 Izadi S, Newcombe R, Kim D, Hilliges O, Molyneaux D, Hodges S, Kohli P, Shotton J, Davison A, Fitzgibbon A (2011) Kinectfusion: real-time dynamic 3D surface reconstruction and interaction. In: ACM SIGGRAPH 2011 talks. ACM, p 23
18.
Zurück zum Zitat Janoch A, Karayev S, Jia Y, Barron JT, Fritz M, Saenko K, Darrell T (2013) A category-level 3D object dataset: putting the kinect to work. In: Consumer depth cameras for computer vision. Springer, pp 141–165 Janoch A, Karayev S, Jia Y, Barron JT, Fritz M, Saenko K, Darrell T (2013) A category-level 3D object dataset: putting the kinect to work. In: Consumer depth cameras for computer vision. Springer, pp 141–165
19.
Zurück zum Zitat Kainz B, Hauswiesner S, Reitmayr G, Steinberger M, Grasset R, Gruber L, Veas E, Kalkofen D, Seichter H, Schmalstieg D (2012) Omnikinect: real-time dense volumetric data acquisition and applications. In: Proceedings of the 18th ACM symposium on virtual reality software and technology. ACM, pp 25–32 Kainz B, Hauswiesner S, Reitmayr G, Steinberger M, Grasset R, Gruber L, Veas E, Kalkofen D, Seichter H, Schmalstieg D (2012) Omnikinect: real-time dense volumetric data acquisition and applications. In: Proceedings of the 18th ACM symposium on virtual reality software and technology. ACM, pp 25–32
20.
Zurück zum Zitat Khoshelham K (2011) Accuracy analysis of kinect depth data. In: ISPRS workshop laser scanning, vol 38, p 1 Khoshelham K (2011) Accuracy analysis of kinect depth data. In: ISPRS workshop laser scanning, vol 38, p 1
21.
Zurück zum Zitat Lai K, Bo L, Ren X, Fox D (2011) A large-scale hierarchical multi-view RGBD-D object dataset. In: IEEE international conference on robotics and automation (ICRA). IEEE, pp 1817–1824 Lai K, Bo L, Ren X, Fox D (2011) A large-scale hierarchical multi-view RGBD-D object dataset. In: IEEE international conference on robotics and automation (ICRA). IEEE, pp 1817–1824
22.
Zurück zum Zitat Lieberknecht S, Huber A, Ilic S, Benhimane S (2011) RGB-D camera-based parallel tracking and meshing. In: ISMAR Lieberknecht S, Huber A, Ilic S, Benhimane S (2011) RGB-D camera-based parallel tracking and meshing. In: ISMAR
23.
Zurück zum Zitat Liu L, Shao L (2013) Learning discriminative representations from RGB-D video data. In: Proceedings of the international joint conference on artificial intelligence (IJCAI) Liu L, Shao L (2013) Learning discriminative representations from RGB-D video data. In: Proceedings of the international joint conference on artificial intelligence (IJCAI)
24.
Zurück zum Zitat Lo R, Rampersad V, Huang J, Mann S (2013) Three dimensional high dynamic range veillance for 3D range-sensing cameras Lo R, Rampersad V, Huang J, Mann S (2013) Three dimensional high dynamic range veillance for 3D range-sensing cameras
25.
Zurück zum Zitat Luber M, Spinello L, Arras KO (2011) People tracking in RGBD-D data with on-line boosted target models. In: IEEE/RSJ international conference on intelligent robots and systems (IROS). IEEE, pp 3844–3849 Luber M, Spinello L, Arras KO (2011) People tracking in RGBD-D data with on-line boosted target models. In: IEEE/RSJ international conference on intelligent robots and systems (IROS). IEEE, pp 3844–3849
26.
Zurück zum Zitat Lysenkov I, Eruhimov V, Bradski GR (2012) Recognition and pose estimation of rigid transparent objects with a kinect sensor. In: Robotics: science and systems Lysenkov I, Eruhimov V, Bradski GR (2012) Recognition and pose estimation of rigid transparent objects with a kinect sensor. In: Robotics: science and systems
27.
Zurück zum Zitat Machado J, Ferreira A (2013) Retrieval of objects captured with low-cost depth-sensing cameras. In: SHREC2013. Springer Machado J, Ferreira A (2013) Retrieval of objects captured with low-cost depth-sensing cameras. In: SHREC2013. Springer
28.
Zurück zum Zitat Macknojia R, Chávez-Aragón A, Payeur P, Laganière R (2013) Calibration of a network of kinect sensors for robotic inspection over a large workspace. In: Proceedings of the IEEE workshop on robot vision (WoRV 2013) Macknojia R, Chávez-Aragón A, Payeur P, Laganière R (2013) Calibration of a network of kinect sensors for robotic inspection over a large workspace. In: Proceedings of the IEEE workshop on robot vision (WoRV 2013)
29.
Zurück zum Zitat Maimone A, Fuchs H (2012) Reducing interference between multiple structured light depth sensors using motion. In: Virtual reality workshops (VR). IEEE, pp 51–54 Maimone A, Fuchs H (2012) Reducing interference between multiple structured light depth sensors using motion. In: Virtual reality workshops (VR). IEEE, pp 51–54
30.
Zurück zum Zitat Martinez M, Stiefelhagen R (2013) Kinect unleashed: getting control over high resolution depth maps Martinez M, Stiefelhagen R (2013) Kinect unleashed: getting control over high resolution depth maps
31.
Zurück zum Zitat Miao D, Fu J, Lu Y, Li S, Chen CW (2012) Texture-assisted kinect depth inpainting. In: IEEE international symposium on circuits and systems (ISCAS). IEEE, pp 604–607 Miao D, Fu J, Lu Y, Li S, Chen CW (2012) Texture-assisted kinect depth inpainting. In: IEEE international symposium on circuits and systems (ISCAS). IEEE, pp 604–607
32.
Zurück zum Zitat Nakamura DALR Multiple 3D data acquisition system setup based on structured ligth technique for immersive videoconferencing applications Nakamura DALR Multiple 3D data acquisition system setup based on structured ligth technique for immersive videoconferencing applications
33.
Zurück zum Zitat Nakazawa M, Mitsugami I, Makihara Y, Nakajima H, Habe H, Yamazoe H, Yagi Y (2012) Dynamic scene reconstruction using asynchronous multiple kinects. In: 21st international conference on pattern recognition (ICPR). IEEE, pp 469–472 Nakazawa M, Mitsugami I, Makihara Y, Nakajima H, Habe H, Yamazoe H, Yagi Y (2012) Dynamic scene reconstruction using asynchronous multiple kinects. In: 21st international conference on pattern recognition (ICPR). IEEE, pp 469–472
34.
Zurück zum Zitat Nathan Silberman PK, Hoiem D, Fergus R (2012) Indoor segmentation and support inference from RGBD images. In: ECCV Nathan Silberman PK, Hoiem D, Fergus R (2012) Indoor segmentation and support inference from RGBD images. In: ECCV
35.
Zurück zum Zitat Negin F, Özdemir F, Akgül CB, Yüksel KA, Erçil A (2013) A decision forest based feature selection framework for action recognition from RGB-depth cameras. In: Image analysis and recognition. Springer, pp 648–657 Negin F, Özdemir F, Akgül CB, Yüksel KA, Erçil A (2013) A decision forest based feature selection framework for action recognition from RGB-depth cameras. In: Image analysis and recognition. Springer, pp 648–657
36.
Zurück zum Zitat Olesen SM, Lyder S, Kraft D, Krüger N, Jessen JB (2012) Real-time extraction of surface patches with associated uncertainties by means of kinect cameras. J Real-Time Image Process 1–14 Olesen SM, Lyder S, Kraft D, Krüger N, Jessen JB (2012) Real-time extraction of surface patches with associated uncertainties by means of kinect cameras. J Real-Time Image Process 1–14
37.
Zurück zum Zitat Ou-Yang T-H, Tsai M-L, Yen C-T, Lin T-T (2011) An infrared range camera-based approach for three-dimensional locomotion tracking and pose reconstruction in a rodent. J Neurosci Methods 201(1):116–123CrossRef Ou-Yang T-H, Tsai M-L, Yen C-T, Lin T-T (2011) An infrared range camera-based approach for three-dimensional locomotion tracking and pose reconstruction in a rodent. J Neurosci Methods 201(1):116–123CrossRef
38.
Zurück zum Zitat Pancham A, Tlale N, Bright G (2012) Mapping and tracking of moving objects in dynamic environments Pancham A, Tlale N, Bright G (2012) Mapping and tracking of moving objects in dynamic environments
39.
Zurück zum Zitat Rafibakhsh N, Gong J, Siddiqui MK, Gordon C, Lee HF (2012) Analysis of xbox kinect sensor data for use on construction sites: depth accuracy and sensor interference assessment. In: Constitution research congress, pp 848–857 Rafibakhsh N, Gong J, Siddiqui MK, Gordon C, Lee HF (2012) Analysis of xbox kinect sensor data for use on construction sites: depth accuracy and sensor interference assessment. In: Constitution research congress, pp 848–857
40.
Zurück zum Zitat Santhanam A, Low D, Kupelian P (2011) Th-c-brc-11: 3D tracking of interfraction and intrafraction head and neck anatomy during radiotherapy using multiple kinect sensors. Med Phys 38:3858CrossRef Santhanam A, Low D, Kupelian P (2011) Th-c-brc-11: 3D tracking of interfraction and intrafraction head and neck anatomy during radiotherapy using multiple kinect sensors. Med Phys 38:3858CrossRef
41.
Zurück zum Zitat Saputra MRU, Putra GD, Santosa PI et al (2012) Indoor human tracking application using multiple depth-cameras. In: International conference on advanced computer science and information systems (ICACSIS). IEEE, pp 307–312 Saputra MRU, Putra GD, Santosa PI et al (2012) Indoor human tracking application using multiple depth-cameras. In: International conference on advanced computer science and information systems (ICACSIS). IEEE, pp 307–312
42.
Zurück zum Zitat Satta R, Pala F, Fumera G, Roli F (2013) Real-time appearance-based person re-identification over multiple kinect TM cameras Satta R, Pala F, Fumera G, Roli F (2013) Real-time appearance-based person re-identification over multiple kinect TM cameras
43.
Zurück zum Zitat Satyavolu S, Bruder G, Willemsen P, Steinicke F (2012) Analysis of IR-based virtual reality tracking using multiple kinects. In: Virtual reality workshops (VR). IEEE, pp 149–150 Satyavolu S, Bruder G, Willemsen P, Steinicke F (2012) Analysis of IR-based virtual reality tracking using multiple kinects. In: Virtual reality workshops (VR). IEEE, pp 149–150
44.
Zurück zum Zitat Schröder Y, Scholz A, Berger K, Ruhl K, Guthe S, Magnor M (2011) Multiple kinect studies. Comput Graph Schröder Y, Scholz A, Berger K, Ruhl K, Guthe S, Magnor M (2011) Multiple kinect studies. Comput Graph
45.
Zurück zum Zitat Sturm J, Engelhard N, Endres F, Burgard W, Cremers D (2012) A benchmark for the evaluation of RGB-D slam systems. In: Proceedings of the IEEE international conference on intelligent robot systems (IROS), pp 573–580 Sturm J, Engelhard N, Endres F, Burgard W, Cremers D (2012) A benchmark for the evaluation of RGB-D slam systems. In: Proceedings of the IEEE international conference on intelligent robot systems (IROS), pp 573–580
46.
Zurück zum Zitat Sturm J, Magnenat S, Engelhard N, Pomerleau F, Colas F, Burgard W, Cremers D, Siegwart R (2011) Towards a benchmark for RGB-D slam evaluation. In: Proceedings of the RGB-D workshop on advanced reasoning with depth cameras at robotics: science and systems conference (RSS), vol 2. Los Angeles, USA, p 3 Sturm J, Magnenat S, Engelhard N, Pomerleau F, Colas F, Burgard W, Cremers D, Siegwart R (2011) Towards a benchmark for RGB-D slam evaluation. In: Proceedings of the RGB-D workshop on advanced reasoning with depth cameras at robotics: science and systems conference (RSS), vol 2. Los Angeles, USA, p 3
47.
Zurück zum Zitat Sumar L, Bainbridge-Smith A (2014) Feasability of fast image processing using multiple kinect cameras on a portable platform. Department of electrical and computer engineering, University. Canterbury, New Zealand Sumar L, Bainbridge-Smith A (2014) Feasability of fast image processing using multiple kinect cameras on a portable platform. Department of electrical and computer engineering, University. Canterbury, New Zealand
48.
Zurück zum Zitat Sung J, Ponce C, Selman B, Saxena A (2011) Human activity detection from RGBD images. In: plan, activity, and intent recognition Sung J, Ponce C, Selman B, Saxena A (2011) Human activity detection from RGBD images. In: plan, activity, and intent recognition
49.
Zurück zum Zitat Susanto W, Rohrbach M, Schiele B (2012) 3D object detection with multiple kinects. In: Computer vision-ECCV 2012. Workshops and demonstrations. Springer, pp 93–102 Susanto W, Rohrbach M, Schiele B (2012) 3D object detection with multiple kinects. In: Computer vision-ECCV 2012. Workshops and demonstrations. Springer, pp 93–102
50.
Zurück zum Zitat Tam G, Cheng Z-Q, Lai Y-K, Langbein F, Liu Y, Marshall A, Martin R, Sun X-F, Rosin P (2012) Registration of 3D point clouds and meshes: a survey from rigid to non-rigid Tam G, Cheng Z-Q, Lai Y-K, Langbein F, Liu Y, Marshall A, Martin R, Sun X-F, Rosin P (2012) Registration of 3D point clouds and meshes: a survey from rigid to non-rigid
51.
Zurück zum Zitat Tong J, Zhou J, Liu L, Pan Z, Yan H (2012) Scanning 3D full human bodies using kinects. EEE Trans Visual Comput Graph 18(4):643–650CrossRef Tong J, Zhou J, Liu L, Pan Z, Yan H (2012) Scanning 3D full human bodies using kinects. EEE Trans Visual Comput Graph 18(4):643–650CrossRef
52.
Zurück zum Zitat Wang J, Zhang C, Zhu W, Zhang Z, Xiong Z, Chou PA (2012) 3D scene reconstruction by multiple structured-light based commodity depth cameras. In: IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE, pp 5429–5432 Wang J, Zhang C, Zhu W, Zhang Z, Xiong Z, Chou PA (2012) 3D scene reconstruction by multiple structured-light based commodity depth cameras. In: IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE, pp 5429–5432
53.
Zurück zum Zitat Wilson AD, Benko H (2010) Combining multiple depth cameras and projectors for interactions on, above and between surfaces. In: Proceedings of the 23nd annual ACM symposium on user interface software and technology. ACM, pp 273–282 Wilson AD, Benko H (2010) Combining multiple depth cameras and projectors for interactions on, above and between surfaces. In: Proceedings of the 23nd annual ACM symposium on user interface software and technology. ACM, pp 273–282
54.
Zurück zum Zitat Ye G, Liu Y, Deng Y, Hasler N, Ji X, Dai Q, Theobalt C (2013) Free-viewpoint video of human actors using multiple handheld kinects. In: IEEE transactions on cybernetics Ye G, Liu Y, Deng Y, Hasler N, Ji X, Dai Q, Theobalt C (2013) Free-viewpoint video of human actors using multiple handheld kinects. In: IEEE transactions on cybernetics
55.
Zurück zum Zitat Zhang L, Sturm J, Cremers D, Lee D (2012) Real-time human motion tracking using multiple depth cameras. In: IEEE/RSJ international conference on intelligent robots and systems (IROS). IEEE, pp 2389–2395 Zhang L, Sturm J, Cremers D, Lee D (2012) Real-time human motion tracking using multiple depth cameras. In: IEEE/RSJ international conference on intelligent robots and systems (IROS). IEEE, pp 2389–2395
56.
Zurück zum Zitat Zhang Z (2012) Microsoft kinect sensor and its effect. IEEE Multimedia 19(2):4–10CrossRef Zhang Z (2012) Microsoft kinect sensor and its effect. IEEE Multimedia 19(2):4–10CrossRef
Metadaten
Titel
A State of the Art Report on Multiple RGB-D Sensor Research and on Publicly Available RGB-D Datasets
verfasst von
Kai Berger
Copyright-Jahr
2014
DOI
https://doi.org/10.1007/978-3-319-08651-4_2