Towards the understanding of object manipulations by means of combining common sense rules and deep networks

Csákvári, Máté and Sárkány, András: Towards the understanding of object manipulations by means of combining common sense rules and deep networks. Conference of PhD Students in Computer Science, (11). pp. 118-121. (2018)

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Abstract

Object detection on images and videos improved remarkably recently. However, state-of-theart methods still have considerable shortcomings: they require training data for each object class, are prone to occlusions and may have high false positive or false negative rates being prohibitive in diverse applications. We study a case that a) has a limited goal and works in a narrow context, b) includes common sense rules on ‘objectness’ and c) exploits state-of-the art deep detectors of different kinds. Our proposed method works on an image sequence from a stationary camera and detects objects that may be manipulated by actors in a scenario. The object types are not known to the system and we consider two actions: “taking an object from a table" and “putting an object onto the table". We quantitatively evaluate our method on manually annotated video segments and present precision and recall scores.

Item Type: Article
Event Title: Conference of PhD students in computer science (11.) (2018) (Szeged)
Journal or Publication Title: Conference of PhD Students in Computer Science
Date: 2018
Volume: 11
Page Range: pp. 118-121
Uncontrolled Keywords: Számítástechnika
Additional Information: Bibliogr.: 121. p. ; összefoglalás angol nyelven
Date Deposited: 2019. Nov. 04. 12:57
Last Modified: 2019. Nov. 04. 12:57
URI: http://acta.bibl.u-szeged.hu/id/eprint/61781

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