Fingerspelling recognition in the wild with iterative visual attention
Table 4: Accuracy comparison between zooming and enlarging in the face ROI setting.
['[ITALIC] R=0.93', 'Zooming', 'Enlarging']
We ran the following experiment to show the benefits of distraction removal obtained by the zooming employed in iterative attention, in addition to the increase in resolution. In particular, we compare the accuracy of zooming at ratio R and enlarging the input images by 1R in the face ROI setting. For this experiment, R is set to 0.93, corresponding to the zooming ratio we use in the first iteration. Comparison on smaller ratios is not feasible due to GPU memory constraints (12GB in our case). For both zooming and enlarging, the resolution of the signing hand is the same. When the prior map is used, the gap between the two approaches is small. This is mainly because distracting portions can be filtered via the motion-based prior in our model. The gain of zooming becomes much larger when we do not use optical flow as a complementary prior, demonstrating the benefit of distraction removal in our approach. Additionally, the motion-based prior has a negligible effect on the accuracy of our approach in this setting.