Recognition performance (mean accuracy ± standard deviation) of the FVs with the GMM and ours (soft objective) codebooks on the Butterflies, corresponding to the Fig 7.</p
<p>Mean (and standard deviation) for recognition performance by Group and Test.</p
Accuracy of Algorithm 1 on the synthetic datasets (left) and the KC dataset (right). Each line denot...
<p>Comparison of accuracy rate of different features extracted with classification algorithms.</p
Recognition performance (mean accuracy ± standard deviation) of the FVs with the GMM and ours (soft ...
Recognition performance (mean accuracy ± standard deviation) of the VLADs with the k-means and ours ...
Recognition performance (mean accuracy ± standard deviation) of the VLADs with the k-means and ours ...
(A) 20 images per category for training. (B) 30 images per category for training. (C) 40 images per ...
(A) 30 images per category for training. (B) 40 images per category for training. (C) 50 images per ...
The objective values of the GMM and ours with the soft objective with respect to the codebook size o...
<p>The mean accuracy values obtained over the 30 bootstrap iterations. Acc – is the overall accuracy...
Mean accuracy (standard deviations) in percentages for each group on the recognition of each emotion...
(A) 20 images per category for training. (B) 30 images per category for training. (C) 40 images per ...
<p>Mean recognition rates(%) and standard deviations of different methods on FRGC database.</p
<p>The average recognition rates (%) and the corresponding standard deviations (%) of different algo...
<p>The average recognition rates (%) and standard deviations (%) of different algorithms on LFW data...
<p>Mean (and standard deviation) for recognition performance by Group and Test.</p
Accuracy of Algorithm 1 on the synthetic datasets (left) and the KC dataset (right). Each line denot...
<p>Comparison of accuracy rate of different features extracted with classification algorithms.</p
Recognition performance (mean accuracy ± standard deviation) of the FVs with the GMM and ours (soft ...
Recognition performance (mean accuracy ± standard deviation) of the VLADs with the k-means and ours ...
Recognition performance (mean accuracy ± standard deviation) of the VLADs with the k-means and ours ...
(A) 20 images per category for training. (B) 30 images per category for training. (C) 40 images per ...
(A) 30 images per category for training. (B) 40 images per category for training. (C) 50 images per ...
The objective values of the GMM and ours with the soft objective with respect to the codebook size o...
<p>The mean accuracy values obtained over the 30 bootstrap iterations. Acc – is the overall accuracy...
Mean accuracy (standard deviations) in percentages for each group on the recognition of each emotion...
(A) 20 images per category for training. (B) 30 images per category for training. (C) 40 images per ...
<p>Mean recognition rates(%) and standard deviations of different methods on FRGC database.</p
<p>The average recognition rates (%) and the corresponding standard deviations (%) of different algo...
<p>The average recognition rates (%) and standard deviations (%) of different algorithms on LFW data...
<p>Mean (and standard deviation) for recognition performance by Group and Test.</p
Accuracy of Algorithm 1 on the synthetic datasets (left) and the KC dataset (right). Each line denot...
<p>Comparison of accuracy rate of different features extracted with classification algorithms.</p
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