面部声音化

Vaishakh Patil, Mohammed Qassim Akhtar, Abhijit Parab, Aisha Fernandes
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引用次数: 1

摘要

本文讨论了人脸片段检测与提取、人脸表情识别与超声处理的集成。本文提出了一种利用haar分类器检测人脸,然后将人脸划分为感兴趣区域(ROI)提取人脸片段的算法。此外,在本项目中,我们提出了一种统计方法来处理光流数据,以获得面部各个特征区域的总体值。该方法消除了对特征边界准确识别的要求。利用光流计算来识别由人类面部表情引起的图像序列中的方向和运动量。然后将这些计算值与表中的值进行比较来估计表达式。得到表达式后;然后通过映射函数将其转换为声音。声音是由简单的MIDI曲调根据分配给每个地区的乐器产生的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sonification of Face
In this paper, the integration of face segments detection and extraction, and facial expression recognition and Sonification are discussed. In this paper, we propose an algorithm that utilizes haar classifiers detecting face followed by dividing face into Regions of interest (ROI) to extract facial segments. Furthermore, in this project, we propose a statistical approach to process the optical flow data to obtain the overall value for the respective feature region in the face. This approach has eliminated the requirement of accurate identification of the feature boundary. Optical flow computations are utilized to identify the directions and the amount of motions in image sequences that are caused by human facial expressions. These calculated values are then compared with the values from table to estimate the expression .Furthermore after getting the expression; these are then converted to sound by mapping functions. Sounds are generated by simple MIDI tunes based on instruments assigned to each region.
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