Abstract:
We present a method to identify human-object interactions involved in complex, fine-grained activities. Our approach benefits from recent improvements in range sensor technology and body trackers to detect and classify important events in a depth video. Combining global motion information with local video analysis, our method is able to recognize the time instants of a video at which a person picks up or puts down an object. We introduce three novel datasets for evaluation and perform extensive experiments with promising results. © Springer International Publishing Switzerland 2014.
Registro:
Documento: |
Artículo
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Título: | Detecting subtle human-object interactions using kinect |
Autor: | Ubalde, S.; Liu, Z.; Mejail, M.; Hancock E.; Bayro-Corrochano E. |
Filiación: | Departamento de Computación, Universidad de Buenos Aires, Buenos Aires, Argentina Microsoft Research, Redmond, United States
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Palabras clave: | Depth sensor; Human-object interaction; Trajectory analysis; Computer vision; Depth sensors; Depth videos; Fine grained; Global motion; Human-object interaction; Range sensors; Trajectory analysis; Video analysis; Pattern recognition |
Año: | 2014
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Volumen: | 8827
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Página de inicio: | 770
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Página de fin: | 777
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Título revista: | 19th Iberoamerican Congress on Pattern Recognition, CIARP 2014
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Título revista abreviado: | Lect. Notes Comput. Sci.
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ISSN: | 03029743
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Registro: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03029743_v8827_n_p770_Ubalde |
Referencias:
- Oreifej, O., Liu, Z., Hon4d: Histogram of oriented 4D normals for activity recognition from depth sequences (2013) CVPR 2013, pp. 716-723
- Wang, J., Liu, Z., Wu, Y., Yuan, J., Mining actionlet ensemble for action recognition with depth cameras (2012) CVPR 2012, pp. 1290-1297
- Vieira, A., Nascimento, E., Oliveira, G., Liu, Z., Campos, M., Stop: Space-time occupancy patterns for 3D action recognition from depth map sequences (2012) CIARP 2012. LNCS, 7441, pp. 252-259. , Alvarez, L., Mejail, M., Gomez, L., Jacobo, J. (eds.),,. Springer, Heidelberg
- Li, W., Zhang, Z., Liu, Z., Action recognition based on a bag of 3D points (2010) CVPR4HB 2010, pp. 9-14
- Sung, J., Ponce, C., Selman, B., Saxena, A., Human activity detection from RGBD images (2011) AAAI workshop on Pattern, , Activity and Intent Recognition, PAIR
- Mehrotra, S., Zhang, Z., Cai, Q., Zhang, C., Chou, P.A., Low-complexity, nearlossless coding of depth maps from kinect-like depth cameras (2011) MMSP, pp. 1-6. , IEEE
- Camplani, M., Salgado, L., Efficient spatio-temporal hole filling strategy for Kinect depth maps (2012) Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, 8290. , (February, Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series
- Gupta, A., Davis, L., Objects in action: An approach for combining action understanding and object perception (2007) CVPR 2007, pp. 1-8
- Gupta, A., Kembhavi, A., Davis, L., Observing human-object interactions: Using spatial and functional compatibility for recognition (2009) PAMI, 31, pp. 1775-1789
- Packer, B., Saenko, K., Koller, D., A combined pose, object, and feature model for action understanding (2012) 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1378-1385. , (June
- Datasets, , http://www-2.dc.uba.ar/grupinv/imagenes/subalde/
- Shotton, J., Sharp, T., Kipman, A., Fitzgibbon, A., Finocchio, M., Blake, A., Cook, M., Moore, R., Real-time human pose recognition in parts from single depth images (2013) CACM, 56, pp. 116-124. , (January
- Perona, P., Malik, J., Scale space and edge detection using anisotropic diffusion (1987) CVWS 1987, pp. 16-22
- Rao, C., Yilmaz, A., Shah, M., View-invariant representation and recognition of actions (2002) IJCV, 50, pp. 203-226. , (NovemberA4 - Chilean Association for Pattern Recognition (AChiRP); CINVESTAV, Campus Guadalajara; Cuban Association for Pattern Recognition (ACRP); INTEL Education; International Association for Pattern Recognition (IAPR); Mexican Association for Computer Vision; Neurocomputing and Robotics (MACVNR); Portuguese Association for Pattern Recognition (APRP); Spanish Association for Pattern Recogntion and Image Analysis (AERFAI); Special Interest Group of the Brazilian Computer Society (SIGPR-SBC)
Citas:
---------- APA ----------
Ubalde, S., Liu, Z., Mejail, M., Hancock E. & Bayro-Corrochano E.
(2014)
. Detecting subtle human-object interactions using kinect. 19th Iberoamerican Congress on Pattern Recognition, CIARP 2014, 8827, 770-777.
Recuperado de https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03029743_v8827_n_p770_Ubalde [ ]
---------- CHICAGO ----------
Ubalde, S., Liu, Z., Mejail, M., Hancock E., Bayro-Corrochano E.
"Detecting subtle human-object interactions using kinect"
. 19th Iberoamerican Congress on Pattern Recognition, CIARP 2014 8827
(2014) : 770-777.
Recuperado de https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03029743_v8827_n_p770_Ubalde [ ]
---------- MLA ----------
Ubalde, S., Liu, Z., Mejail, M., Hancock E., Bayro-Corrochano E.
"Detecting subtle human-object interactions using kinect"
. 19th Iberoamerican Congress on Pattern Recognition, CIARP 2014, vol. 8827, 2014, pp. 770-777.
Recuperado de https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03029743_v8827_n_p770_Ubalde [ ]
---------- VANCOUVER ----------
Ubalde, S., Liu, Z., Mejail, M., Hancock E., Bayro-Corrochano E. Detecting subtle human-object interactions using kinect. Lect. Notes Comput. Sci. 2014;8827:770-777.
Available from: https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03029743_v8827_n_p770_Ubalde [ ]