Recognizing Cultural Events in Images: A Study of Image Categorization Models

Heeyoung Kwon, Kiwon Yun, Minh Hoai, Dimitris Samaras; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2015, pp. 51-57

Abstract

The goal of this work is to study recognition of cultural events represented in still images. We pose cultural event recognition as an image categorization problem, and we study the performance of several state-of-the-art image categorization approaches, including Spatial Pyramid Matching and Regularized Max Pooling. We consider SIFT and color features as well as the recently proposed CNN features. Experiments on the ChaLearn dataset of 50 cultural events, we find that Regularized Max Pooling with CNN features achieves the best performance.

Related Material

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[bibtex]
@InProceedings{Kwon_2015_CVPR_Workshops,
author = {Kwon, Heeyoung and Yun, Kiwon and Hoai, Minh and Samaras, Dimitris},
title = {Recognizing Cultural Events in Images: A Study of Image Categorization Models},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2015}
}