  In this paper, we propose an innovative end-to-end subtitle detection and
recognition system for videos in East Asian languages. Our end-to-end system
consists of multiple stages. Subtitles are firstly detected by a novel image
operator based on the sequence information of consecutive video frames. Then,
an ensemble of Convolutional Neural Networks (CNNs) trained on synthetic data
is adopted for detecting and recognizing East Asian characters. Finally, a
dynamic programming approach leveraging language models is applied to
constitute results of the entire body of text lines. The proposed system
achieves average end-to-end accuracies of 98.2% and 98.3% on 40 videos in
Simplified Chinese and 40 videos in Traditional Chinese respectively, which is
a significant outperformance of other existing methods. The near-perfect
accuracy of our system dramatically narrows the gap between human cognitive
ability and state-of-the-art algorithms used for such a task.
