An Algorithm for Auto-threshold for Mouth ROI

Shilpa Sonawane, P. Malathi, B.B. Musmade
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Abstract

Lip reading technology is best possible solution of speech recognition in noisy environments. Lip reading is a methodology to interpret by lip movement without the involvement of audio. The accuracy of lip-reading technology is based on accurate mouth region of interest (ROI). Viola Jones algorithm is used for mouth region extraction. The accuracy by viola jones is affected by merge threshold parameter of cascade object detector. Due to incorrect threshold multiple bounding boxes appears for mouth ROI. The correct selection of merge threshold leads to single bounding box on mouth region. The technique to find appropriate threshold to extract mouth ROI is presented in this paper. The algorithm is applied on GRID and LRW dataset. Experiment is tested on both frontal and profile face video frames. The accuracy obtained on frontal face frames from GRID dataset is 100 % while 86.20% accuracy achieved with profile video frames from LRW dataset.
一种口腔ROI自动阈值算法
唇读技术是嘈杂环境下语音识别的最佳解决方案。唇读是一种在没有声音参与的情况下,通过唇动进行解读的方法。唇读技术的准确性基于准确的口腔感兴趣区域(ROI)。采用维奥拉琼斯算法提取口腔区域。串级目标检测器的合并阈值参数影响了中提琴琼斯算法的精度。由于不正确的阈值,出现了多个边界框的口腔ROI。合并阈值的正确选择导致口区边界框单一。提出了一种寻找合适的阈值提取口腔ROI的方法。将该算法应用于GRID和LRW数据集。实验在正面和侧面视频帧上进行了测试。栅格数据集对正面人脸帧的准确率为100%,LRW数据集对侧面视频帧的准确率为86.20%。
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