ML Anthology

Recognizing Primitive Interactions by Exploring Actor-Object States

Roman Filipovych, Eraldo Ribeiro
CVPR 2008
doi:10.1109/CVPR.2008.4587726 /cvpr/2008/filipovych2008cvpr-recognizing/

Abstract

In this paper, we present a solution to the novel problem of recognizing primitive actor-object interactions from videos. Here, we introduce the concept of actor-object states. Our method is based on the observation that at the moment of physical contact, both the motion and the appearance of actors are constrained by the target object. We propose a probabilistic framework that automatically learns models in such constrained states. We use joint probability distributions to represent both actor and object appearances as well as their intrinsic spatio-temporal configurations. Finally, we demonstrate the applicability of our approach on series of human-object interaction classification experiments.

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Cite

Text

Filipovych and Ribeiro. "Recognizing Primitive Interactions by Exploring Actor-Object States." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2008. doi:10.1109/CVPR.2008.4587726

Markdown

[Filipovych and Ribeiro. "Recognizing Primitive Interactions by Exploring Actor-Object States." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2008.](https://mlanthology.org/cvpr/2008/filipovych2008cvpr-recognizing/) doi:10.1109/CVPR.2008.4587726

BibTeX

@inproceedings{filipovych2008cvpr-recognizing,
  title     = {{Recognizing Primitive Interactions by Exploring Actor-Object States}},
  author    = {Filipovych, Roman and Ribeiro, Eraldo},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2008},
  doi       = {10.1109/CVPR.2008.4587726},
  url       = {https://mlanthology.org/cvpr/2008/filipovych2008cvpr-recognizing/}
}