3D Convolutional Neural Networks for Human Action Recognition

Volume: 35, Issue: 1, Pages: 221 - 231
Published: Jan 1, 2013
Abstract
We consider the automated recognition of human actions in surveillance videos. Most current methods build classifiers based on complex handcrafted features computed from the raw inputs. Convolutional neural networks (CNNs) are a type of deep model that can act directly on the raw inputs. However, such models are currently limited to handling 2D inputs. In this paper, we develop a novel 3D CNN model for action recognition. This model extracts...
Paper Details
Title
3D Convolutional Neural Networks for Human Action Recognition
Published Date
Jan 1, 2013
Volume
35
Issue
1
Pages
221 - 231
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