Bernhard Fröba, T. Kastner, W. Zink, Christian Kiiblbeck
{"title":"用于人脸分割的实时主动形状模型","authors":"Bernhard Fröba, T. Kastner, W. Zink, Christian Kiiblbeck","doi":"10.1109/ICIP.2001.958989","DOIUrl":null,"url":null,"abstract":"In this work we tackle the problem of real-time alignment of active shape models to new object instances at video frame rate. To achieve this we use edge orientation information as the basic image feature. Unlike in the original active shape framework we incorporate the image features directly into the model vector. We also introduce a new update rule for a model point in a local surrounding. We demonstrate the effectiveness of the proposed approach with a face segmentation task. There we are able to fit a new model face on average within 20 msec on 500 MHz Pentium II PC if the initial model position and size does not deviate too much from the true position. The latter is assured by a face detection step which is carried out before the active shape alignment.","PeriodicalId":291827,"journal":{"name":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Real-time active shape models for face segmentation\",\"authors\":\"Bernhard Fröba, T. Kastner, W. Zink, Christian Kiiblbeck\",\"doi\":\"10.1109/ICIP.2001.958989\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work we tackle the problem of real-time alignment of active shape models to new object instances at video frame rate. To achieve this we use edge orientation information as the basic image feature. Unlike in the original active shape framework we incorporate the image features directly into the model vector. We also introduce a new update rule for a model point in a local surrounding. We demonstrate the effectiveness of the proposed approach with a face segmentation task. There we are able to fit a new model face on average within 20 msec on 500 MHz Pentium II PC if the initial model position and size does not deviate too much from the true position. The latter is assured by a face detection step which is carried out before the active shape alignment.\",\"PeriodicalId\":291827,\"journal\":{\"name\":\"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-10-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIP.2001.958989\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.2001.958989","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
摘要
在这项工作中,我们以视频帧率解决了活动形状模型与新对象实例的实时对齐问题。为了实现这一点,我们使用边缘方向信息作为基本图像特征。与原始的活动形状框架不同,我们将图像特征直接合并到模型向量中。我们还引入了局部环境中模型点的更新规则。我们通过人脸分割任务证明了所提出方法的有效性。在500 MHz的Pentium II PC上,如果初始模型位置和尺寸没有偏离真实位置太多,我们可以在平均20毫秒内适应一个新的模型面。后者通过在主动形状对齐之前进行的人脸检测步骤来保证。
Real-time active shape models for face segmentation
In this work we tackle the problem of real-time alignment of active shape models to new object instances at video frame rate. To achieve this we use edge orientation information as the basic image feature. Unlike in the original active shape framework we incorporate the image features directly into the model vector. We also introduce a new update rule for a model point in a local surrounding. We demonstrate the effectiveness of the proposed approach with a face segmentation task. There we are able to fit a new model face on average within 20 msec on 500 MHz Pentium II PC if the initial model position and size does not deviate too much from the true position. The latter is assured by a face detection step which is carried out before the active shape alignment.