Improving performance with different length templates using both of correlation and absolute difference on similar play estimation - Emerging Trends in Image Processing, Computer Vision, and Pattern Recognition - page 407

Table 3
Performance with Absolute Difference

Length Recall Precision F-Measure

15 1.000 0.190 0.319

20 0.988 0.190 0.318

25 0.976 0.189 0.316

30 0.970 0.186 0.312

40 0.976 0.180 0.303

5.6 Combination Both of Correlations and Absolute Differences
For retrieving the precise pitches in videos, we need to use the correlation-based similarity.
Combining the correlation based similarity and the absolute difference based similarity, we
can improve the performance of the similar pitch retrieval.
Using the correlation based similarity or the absolute difference based similarity, we have
no difficulties to find the proper set of thresholds. In the correlation based similarity or the ab-
solute difference based similarity, two thresholds work in each X - and Y -direction motions.
We use logical conjunction to combine the correlation-based similarity and the absolute
difference-based similarity. We can use logical disjunction. However, minimum is the exten-
sion of logical conjunction. We select logical conjunction in this paper. We have four thresholds
in the combination. It is difficult to optimize all thresholds at once with short processing time.
We divide the optimization of thresholds into two steps. They are the correlation-based simil-
arity threshold optimization, and the absolute difference-based one.
First, we optimize the thresholds in the absolute difference based similarity. Then, we do
ones in the correlation-based similarity. In the absolute difference based experiments, the re-
calls are high enough. This leads the decision. Of cause, there is no difference on the results
between the correlation based first and the absolute difference based first
Table 4 shows the result of the experiments. The templates are same in the previous experi-
ments. Using the same length templates in absolute difference and correlation, the F-measure
is 0.865. In number, there is 158 recalls and 39 errors. The error retrieval rate is 0.000297. This
is 99.97% precision. This precision is very high. In the best mix of the templates' lengths, the
absolute difference measure uses the 15 frames in the length of the template. The correlation
one uses 30 frames in the length of the template. The range of the correlation's template in-
cludes the one of the absolute difference's one. Using the best mix both of absolute difference
and correlation, the F-measure is 0.910. In number, there is 151 recalls and 13 errors. This error
retrieval rate is 0.0000981. This is 99.99% precision. The number of error retrievals decreases
26. This is 67% decrease.