Detecting subtle human-object interactions using kinect
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...
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2014
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| Acceso en línea: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03029743_v8827_n_p770_Ubalde http://hdl.handle.net/20.500.12110/paper_03029743_v8827_n_p770_Ubalde |
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paper:paper_03029743_v8827_n_p770_Ubalde |
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dspace |
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paper:paper_03029743_v8827_n_p770_Ubalde2023-06-08T15:28:55Z Detecting subtle human-object interactions using kinect 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 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. 2014 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03029743_v8827_n_p770_Ubalde http://hdl.handle.net/20.500.12110/paper_03029743_v8827_n_p770_Ubalde |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
| collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
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 |
| spellingShingle |
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 Detecting subtle human-object interactions using kinect |
| topic_facet |
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 |
| description |
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. |
| title |
Detecting subtle human-object interactions using kinect |
| title_short |
Detecting subtle human-object interactions using kinect |
| title_full |
Detecting subtle human-object interactions using kinect |
| title_fullStr |
Detecting subtle human-object interactions using kinect |
| title_full_unstemmed |
Detecting subtle human-object interactions using kinect |
| title_sort |
detecting subtle human-object interactions using kinect |
| publishDate |
2014 |
| url |
https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03029743_v8827_n_p770_Ubalde http://hdl.handle.net/20.500.12110/paper_03029743_v8827_n_p770_Ubalde |
| _version_ |
1768544594788614144 |