<jupyter_start><jupyter_text>Comparison of video summaries with different segmentation methods: Uniform vs KTSmethod A: Video summaries generated using random scoring with uniform segmentationmethod B: Video summaries generated using random scoring with KTS segmentationscore:- 2 method A better than method B- 0: method A is eqally good (bad) to B- -2: method A worse than method B<jupyter_code>sub_df = df[(df.method_a == 'r_uni') & (df.method_b == 'r_kts')]
answer = sub_df.answer
answer_count = answer.value_counts()
index = np.arange(-2, 3)
plt.bar(index,
        answer_count[index],
        color=sns.diverging_palette(10, 220, n=5))
plt.title('uniform vs KTS: avg=%.2f'%answer.mean())
plt.xticks(np.arange(-2, 3), ['-2\n{} better'.format('KTS'),
                              '-1', '0', '1',
                              '2\n{} better'.format('Uniform')])
plot_score_barh('r_uni', 'r_kts', '(A) Uniform segmentation vs. (B) KTS segmentation')<jupyter_output><empty_output><jupyter_text>Comparison of summaries using different scoring method: Random scoring vs DR-DSNmethod A: Video summaries generated using random scoring with KTS segmentationmethod B: Video summaries generated using DR-DSN scoring with KTS segmentationscore:- 2 method A better than method B- 0: method A is eqally good (bad) to B- -2: method A worse than method B<jupyter_code># summary
sub_df = df[(df.method_a == 'r_kts') & (df.method_b == 'drdsn')]
answer = sub_df.answer
answer_count = answer.value_counts()
plt.bar(index,
        answer_count[index],
        color=sns.diverging_palette(10, 220, n=5))
plt.title('random vs drdsn: avg=%.2f'%answer.mean())
plt.xticks(np.arange(-2, 3), ['-2\n{} better'.format('DR-DSN'),
                              '-1', '0', '1',
                              '2\n{} better'.format('Random')])
plot_score_barh('r_kts', 'drdsn', '(A) random scoring with KTS segmentation vs. (B) DR-DSN')<jupyter_output><empty_output><jupyter_text>Comparison between randomized summaries vs human method A: Video summaries generated using random scoring with KTS segmentationmethod B: Manually created video summariesscore:- 2 method A better than method B- 0: method A is eqally good (bad) to B- -2: method A worse than method B<jupyter_code># summary
sub_df = df[(df.method_a == 'r_kts') & (df.method_b == 'h_avg')]
answer = sub_df.answer
answer_count = answer.value_counts()
plt.bar(index,
        answer_count[index],
        color=sns.diverging_palette(10, 220, n=5))
plt.title('random vs human: avg=%.2f'%answer.mean())
plt.xticks(np.arange(-2, 3), ['-2\n{} better'.format('Human'),
                              '-1', '0', '1',
                              '2\n{} better'.format('Random')])
plot_score_barh('r_kts', 'h_avg', '(A) random scoring with KTS segmentation vs. (B) human summary')<jupyter_output><empty_output>
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