用于动作识别的高阶几何图像特征表示

2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR) Pub Date : 2013-12-01 DOI:10.1109/SOCPAR.2013.7054140

N. N. A. Sjarif, S. Z. M. Hashim, S. Shamsuddin, A. Ralescu

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引用次数: 0

摘要

基于Hu矩不变量的高阶图像特征已经成功地应用于各种图像分析任务中。本研究提出了一种不变量对图像的不等缩放的应用，用于构造适合动作识别的图像特征。这些特征是为视频图像计算的，可以用于分类。实验结果表明，与传统的几何不变量相比，该方法是有效的，而且精度更高。

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Higher order geometrical image features representation for action recognition

Higher order image features based on Hu moment invariants have been used successfully in a variety of image analysis tasks. This study presents the application of an invariant to unequal rescaling of the image in constructing image features suitable for action recognition. These features are computed for video images and can be used for classification. Experimental results suggest that this approach is effective and more accurate when compared with traditional geometric invariants.

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2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR)

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