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Representing Pairwise Spatial and Temporal Relations for Action Recognition

Pyry K. Matikainen, Martial Hebert and Rahul Sukthankar
Carnegie Mellon University, European Conference on Computer Vision 2010 (ECCV 2010), September, 2010

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Abstract

The popular bag-of-words paradigm for action recognition tasks is based on building histograms of quantized features, typically at the cost of discarding all information about relationships between them. However, although the bene cial nature of including these relationships seems obvious, in practice nding good representations for feature relationships in video is di cult. We propose a simple and computationally efficient method for expressing pairwise relationships between quantized features that combines the power of discriminative representations with key aspects of Na ve Bayes. We demonstrate how our technique can augment both appearance- and motion-based features, and that it significantly improves performance on both types of features.

BibTeX Reference
@conference{Matikainen-2010-10525,
title = {Representing Pairwise Spatial and Temporal Relations for Action Recognition},
author = {Pyry K. Matikainen and Martial Hebert and Rahul Sukthankar},
booktitle = {European Conference on Computer Vision 2010 (ECCV 2010)},
keyword = {action recognition, spatial relationships},
school = {Robotics Institute , Carnegie Mellon University},
month = {September},
year = {2010},
address = {Pittsburgh, PA},
}
2017-09-13T10:40:37+00:00