Which are the best view-invariant gait algorithms published till date? This is with respect to view-invariance and resilience to covariate factors like carrying condition and clothing condition; preferably one that uses CASIA Dataset B.
The following are the papers that are recently published which I think includes the state of the art but is there any other publication that outperforms these values?
Author Normal Bag Coat Mean
Dupuis et al. 97.11 75.16 84.49 85.59
Choudhury et al. 99.55 87.09 69.09 85.24
Rida et al. 97.39 75.08 86.28 86.25
The above are the averages taken from all 11 angles of the CASIA-B.
References:
Y. Dupuis, X. Savatier, and P. Vasseur, “Feature subset selection applied to model-free gait recognition,” Image and vision computing, vol. 31, no. 8, pp. 580–591, 2013.
S.D. Choudhury and T. Tjahjadi, “Robust view-invariant multiscale gait recognition,” Pattern Recognition, vol. 48, no. 3, pp. 798–811, 2015.
I. Rida, X. Jiang, and G. L. Marcialis, “Human body part selection by group lasso of motion for model-free gait recognition,” IEEE Signal Processing Letters, vol. 23, no. 1, pp. 154–158, 2016.
I would also suggest looking at the deep learning approaches to gait recognition (such as semantic segmentation and labeling using CNNs)
It is also advisable to observe the amount of movement considering the acceleration
Dear Dr. Ramachandra and Mr. Romero,
Thank you for posting but I'm looking for articles published with results related to gait recognition using the CASIA-B dataset.
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