Discriminative human action classification using locality-constrained linear coding

Rahmani, Hossein and Huynh, Du Q. and Mahmood, Arif and Mian, Ajmal (2016) Discriminative human action classification using locality-constrained linear coding. Pattern Recognition Letters, 72. pp. 62-71. ISSN 0167-8655

Full text not available from this repository.


We propose a Locality-constrained Linear Coding (LLC) based algorithm that captures discriminative information of human actions in spatio-temporal subsequences of videos. The input video is divided into equally spaced overlapping spatio-temporal subsequences. Each subsequence is further divided into blocks and then cells. The spatio-temporal information in each cell is represented by a Histogram of Oriented 3D Gradients (HOG3D). LLC is then used to encode each block. We show that LLC gives more stable and repetitive codes compared to the standard Sparse Coding. The final representation of a video sequence is obtained using logistic regression with ℓ2regularization and classification is performed by a linear SVM. The proposed algorithm is applicable to conventional and depth videos. Experimental comparison with ten state-of-the-art methods on three depth video and two conventional video databases shows that the proposed method consistently achieves the best performance.

Item Type:
Journal Article
Journal or Publication Title:
Pattern Recognition Letters
Uncontrolled Keywords:
ID Code:
Deposited By:
Deposited On:
11 Jul 2018 10:40
Last Modified:
22 Nov 2022 06:06