公开(公告)号：US08593523B2

公开(公告)日：2013-11-26

申请号：US13070489

申请日：2011-03-24

Applicant: Shian Wan ,  Yuan-Shi Liao ,  Yea-Shuan Huang ,  Shun-Hsu Chuang

Inventor： Shian Wan ,  Yuan-Shi Liao ,  Yea-Shuan Huang ,  Shun-Hsu Chuang

IPC: H04N5/225 ,  H04N5/228 ,  G06K9/00 ,  G06K9/46 ,  G06K9/66 ,  G06K9/36

CPC classification number: H04N5/23219 ,  G06K9/00315

Abstract: A method and an apparatus for capturing facial expressions are provided, in which different facial expressions of a user are captured through a face recognition technique. In the method, a plurality of sequentially captured images containing human faces is received. Regional features of the human faces in the images are respectively captured to generate a target feature vector. The target feature vector is compared with a plurality of previously stored feature vectors to generate a parameter value. When the parameter value is higher than a threshold, one of the images is selected as a target image. Moreover, a facial expression recognition and classification procedures can be further performed. For example, the target image is recognized to obtain a facial expression state, and the image is classified according to the facial expression state.

Abstract translation: 提供一种用于捕获面部表情的方法和装置，其中通过面部识别技术捕获用户的不同面部表情。 在该方法中，接收包含人脸的多个顺序捕获的图像。 分别捕获图像中人脸的区域特征以产生目标特征向量。 将目标特征向量与多个先前存储的特征向量进行比较以生成参数值。 当参数值高于阈值时，选择其中一个图像作为目标图像。 此外，可以进一步执行面部表情识别和分类程序。 例如，识别目标图像以获得面部表情状态，并且根据面部表情状态对图像进行分类。

公开(公告)号：US07929729B2

公开(公告)日：2011-04-19

申请号：US11695573

申请日：2007-04-02

Applicant: Yea-Shuan Huang ,  Hao-Ying Cheng ,  Po-Feng Cheng ,  Shih-Chun Wang

Inventor： Yea-Shuan Huang ,  Hao-Ying Cheng ,  Po-Feng Cheng ,  Shih-Chun Wang

IPC: G06K9/00 ,  G06K9/46

CPC classification number: G06K9/38

Abstract: A method of image processing, the method comprising receiving an image frame including a plurality of pixels, each of the plurality of pixels including an image information, conducting a first extraction based on the image information to identify foreground pixels related to a foreground object in the image frame and background pixels related to a background of the image frame, scanning the image frame in regions, identifying whether each of the regions includes a sufficient number of foreground pixels, identifying whether each of regions including a sufficient number of foreground pixels includes a foreground object, clustering regions including a foreground object into at least one group, each of the at least one group corresponding to a different foreground object in the image frame, and conducting a second extraction for each of at least one group to identify whether a foreground pixel in the each of the at least one group is to be converted to a background pixel.

Abstract translation: 一种图像处理方法，所述方法包括：接收包括多个像素的图像帧，所述多个像素中的每一个包括图像信息，基于所述图像信息进行第一提取，以识别与所述前景对象相关的前景像素 与图像帧的背景相关的图像帧和背景像素，扫描区域中的图像帧，识别每个区域是否包含足够数量的前景像素，识别包括足够数量的前景像素的每个区域是否包括前景 对象，将包括前景对象的聚类区域分成至少一个组，所述至少一个组中的每一个对应于所述图像帧中的不同前景对象，并且针对至少一个组中的每一个进行第二抽取以识别前景像素 在至少一个组中的每一个将被转换为背景像素。

公开(公告)号：US08311358B2

公开(公告)日：2012-11-13

申请号：US12835263

申请日：2010-07-13

Applicant: Yea-Shuan Huang ,  Chu-Yun Li

Inventor： Yea-Shuan Huang ,  Chu-Yun Li

IPC: G06K9/40

CPC classification number: G06K9/52 ,  G06K9/4609

Abstract: The present invention provides a method for extracting an image texture signal, a method for identifying image and a system for identifying an image. The method for extracting an image texture signal comprises the following steps: extracting a first image signal; employing a first operation procedure to the first image signal to obtain a second image signal; employing a second operation procedure to the second image signal to obtain a third image signal; employing a third operation procedure to the third image signal to obtain a fourth image signal; outputting the fourth image signal. Therefore, the first image signal is transformed to the fourth image signal via the method for extracting an image texture signal.

Abstract translation: 本发明提供了一种用于提取图像纹理信号的方法，用于识别图像的方法和用于识别图像的系统。 提取图像纹理信号的方法包括以下步骤：提取第一图像信号; 对所述第一图像信号采用第一操作过程以获得第二图像信号; 对所述第二图像信号采用第二操作过程以获得第三图像信号; 对第三图像信号采用第三操作过程以获得第四图像信号; 输出第四图像信号。 因此，通过提取图像纹理信号的方法将第一图像信号变换为第四图像信号。

公开(公告)号：US20120169895A1

公开(公告)日：2012-07-05

申请号：US13070489

申请日：2011-03-24

Applicant: Shian Wan ,  Yuan-Shi Liao ,  Yea-Shuan Huang ,  Shun-Hsu Chuang

Inventor： Shian Wan ,  Yuan-Shi Liao ,  Yea-Shuan Huang ,  Shun-Hsu Chuang

IPC: H04N5/228 ,  G06K9/68

CPC classification number: H04N5/23219 ,  G06K9/00315

Abstract: A method and an apparatus for capturing facial expressions are provided, in which different facial expressions of a user are captured through a face recognition technique. In the method, a plurality of sequentially captured images containing human faces is received. Regional features of the human faces in the images are respectively captured to generate a target feature vector. The target feature vector is compared with a plurality of previously stored feature vectors to generate a parameter value. When the parameter value is higher than a threshold, one of the images is selected as a target image. Moreover, a facial expression recognition and classification procedures can be further performed. For example, the target image is recognized to obtain a facial expression state, and the image is classified according to the facial expression state.

Abstract translation: 提供一种用于捕获面部表情的方法和装置，其中通过面部识别技术捕获用户的不同面部表情。 在该方法中，接收包含人脸的多个顺序拍摄的图像。 分别捕获图像中人脸的区域特征以产生目标特征向量。 将目标特征向量与多个先前存储的特征向量进行比较以生成参数值。 当参数值高于阈值时，选择其中一个图像作为目标图像。 此外，可以进一步执行面部表情识别和分类程序。 例如，识别目标图像以获得面部表情状态，并且根据面部表情状态对图像进行分类。

公开(公告)号：US20050141762A1

公开(公告)日：2005-06-30

申请号：US10878321

申请日：2004-06-29

Applicant: Hung-Xin Zhao ,  Yea-Shuan Huang ,  Chung-Mou Pengwu

Inventor： Hung-Xin Zhao ,  Yea-Shuan Huang ,  Chung-Mou Pengwu

IPC: G06K9/00 ,  G06K9/20 ,  G06K9/46

CPC classification number: G06K9/00234 ,  G06K9/2027 ,  G06K9/4652

Abstract: A method for adjusting image acquisition parameters to optimize object extraction is disclosed, which is applied to an object characterized by forming a specific cluster in a color coordinate space after performing a coordinate projection, and thus the specific cluster contributes to a specific color model, such as a human skin color model. This method first locates a target object within a search window in a selected image. Then applies the specific color model to obtain the image acquisition parameter(s) according to the color distribution and features of the target object. Therefore, the image is transformed according to the adjusted image acquisition parameter(s). Consequently, a complete and clear target object can be extracted from the transformed image by applying the specific color model, and the follow-up images having the same image acquisition conditions with the aforesaid image can also be transformed according to the same image acquisition parameter(s).

Abstract translation: 公开了一种用于调整图像获取参数以优化对象提取的方法，其应用于在执行坐标投影之后在颜色坐标空间中形成特定簇的对象，并且因此特定的簇有助于特定的颜色模型，例如 作为人体肤色模型。 该方法首先在所选图像的搜索窗口内定位目标对象。 然后根据目标对象的颜色分布和特征，应用特定颜色模型获取图像采集参数。 因此，根据调整后的图像获取参数来变换图像。 因此，可以通过应用特定颜色模型从变换图像中提取完整且清晰的目标对象，并且具有与上述图像相同的图像获取条件的后续图像也可以根据相同的图像获取参数（ s）。

公开(公告)号：US5940535A

公开(公告)日：1999-08-17

申请号：US741740

申请日：1996-10-31

Applicant: Yea-Shuan Huang

Inventor： Yea-Shuan Huang

IPC: G06K9/62 ,  G06K9/46

CPC classification number: G06K9/6284 ,  G06K9/6272

Abstract: A design for a high reliability recognition system utilizes two optimized thresholds for each class k of a prototype data base. One threshold is a class region threshold CR.sub.k and the other is a dis-ambiguity threshold DA.sub.k. CR.sub.k specifies a constrained region belonging to a class k, and DA.sub.k corresponds to a value with which a sample belonging to class k can be correctly recognized with a high level of confidence. During recognition, if the distance D(x, r.sub.M) between an input sample x and the representative prototype r.sub.M of a nearest class M is larger than the class region threshold CR.sub.M, x will be rejected. Furthermore, if the distance D(x, r.sub.M) is subtracted from the distance D(x, r.sub.S) between x and the representative prototype r.sub.S of a second nearest class S, the resulting distance difference must be greater than the dis-ambiguity threshold DA.sub.M, or x will be rejected. An inventive algorithm is used to compute optimum thresholds CR.sub.k and DA.sub.k for each class k. The algorithm is based on minimizing a cost function of a recognition error analysis. Experiments were performed to verify the feasibility and effectiveness of the inventive method.

Abstract translation: 高可靠性识别系统的设计为原型数据库的每个类别k使用两个优化的阈值。 一个阈值是类区域阈值CRk，另一个是歧义阈值DAk。 CRk指定属于类k的约束区域，DAk对应于以高置信度正确识别属于类别k的样本的值。 在识别期间，如果输入样本x和最近类M的代表原型rM之间的距离D（x，rM）大于类区域阈值CRM，则x将被拒绝。 此外，如果从x与第二最近类别S的代表原型rS之间的距离D（x，rS）中减去距离D（x，rM），则所得到的距离差必须大于歧义阈值DAM ，否则x将被拒绝。 使用本发明的算法来计算每个类k的最佳阈值CRk和DAk。 该算法基于最小化识别误差分析的成本函数。 进行实验以验证本发明方法的可行性和有效性。

公开(公告)号：US08929597B2

公开(公告)日：2015-01-06

申请号：US13527429

申请日：2012-06-19

Applicant: Yea-Shuan Huang ,  Yu-Chung Chen

Inventor： Yea-Shuan Huang ,  Yu-Chung Chen

IPC: G06K9/00

CPC classification number: G06K9/34 ,  G06T7/246 ,  G06T2207/10016

Abstract: A method of object tracking is provided with creating areas of a tracking object and a non-tracking object respectively; determining a state of the tracking object and the non-tracking object is separation, proximity, or overlap; creating at least one separation template image of a separation area of the tracking object and/or the non-tracking object if the tracking object is proximate the non-tracking object; fetching all feature points of an overlapping area of the tracking object and the non-tracking object if the tracking object and the non-tracking object overlap; performing a match on each of the feature points and the separation template image so as to calculate a corresponding matching error score respectively; and comparing the matching error score of each feature point with that of the separation template image so as to determine whether the feature points belong to the tracking object or the non-tracking object.

Abstract translation: 提供了一种对象跟踪的方法，分别创建跟踪对象和非跟踪对象的区域; 确定跟踪对象和非跟踪对象的状态是分离，接近或重叠; 如果跟踪对象靠近非跟踪对象，则创建跟踪对象和/或非跟踪对象的分离区域的至少一个分离模板图像; 如果跟踪对象和非跟踪对象重叠，则获取跟踪对象和非跟踪对象的重叠区域的所有特征点; 在每个特征点和分离模板图像上执行匹配，以便分别计算相应的匹配误差得分; 并且将每个特征点的匹配误差分数与分离模板图像的匹配误差分数进行比较，以确定特征点是否属于跟踪对象或非跟踪对象。

公开(公告)号：US20130259324A1

公开(公告)日：2013-10-03

申请号：US13527454

申请日：2012-06-19

Applicant: Yea-Shuan Huang ,  Kuo-Ta Peng

Inventor： Yea-Shuan Huang ,  Kuo-Ta Peng

IPC: G06K9/62

CPC classification number: G06K9/00281 ,  G06K9/00288

Abstract: A method for face recognition is provided with collecting a match facial image; retrieving a reference image from image records of a database or an input image; selecting one or more facial features from each of the match facial image and the reference image; obtaining at least one match facial feature and a match deviation of the reference image corresponding to the facial features of the match facial image; creating a match geometric model and a reference geometric model; obtaining a model deviation by comparing the match geometric model and the reference geometric model; and employing a match deviation and a model deviation to obtain a recognition score based on a predetermined rule. The method involves a two-way face recognition by integrating facial features of block matching with geometric model comparison. It employs relationship of match deviation and model deviation.

公开(公告)号：US20130259302A1

公开(公告)日：2013-10-03

申请号：US13527429

申请日：2012-06-19

Applicant: Yea-Shuan Huang ,  Yu-Chung Chen

Inventor： Yea-Shuan Huang ,  Yu-Chung Chen

IPC: G06K9/46

CPC classification number: G06K9/34 ,  G06T7/246 ,  G06T2207/10016

Abstract: A method of object tracking is provided with creating areas of a tracking object and a non-tracking object respectively; determining a state of the tracking object and the non-tracking object is separation, proximity, or overlap; creating at least one separation template image of a separation area of the tracking object and/or the non-tracking object if the tracking object is proximate the non-tracking object; fetching all feature points of an overlapping area of the tracking object and the non-tracking object if the tracking object and the non-tracking object overlap; performing a match on each of the feature points and the separation template image so as to calculate a corresponding matching error score respectively; and comparing the matching error score of each feature point with that of the separation template image so as to determine whether the feature points belong to the tracking object or the non-tracking object.

公开(公告)号：US07113637B2

公开(公告)日：2006-09-26

申请号：US09935683

申请日：2001-08-24

Applicant: Yea-Shuan Huang ,  Chun-Wei Hsieh

Inventor： Yea-Shuan Huang ,  Chun-Wei Hsieh

IPC: G06K9/00

CPC classification number: G06K9/6292 ,  G06K9/00221 ,  G06K9/00973

Abstract: In order to improve pattern recognition, various kinds of transformations are performed on an input object. One or more recognition algorithms are then performed on the input object transforms in addition to the input object itself. By performing recognition algorithms on an input object and its transforms, a more comprehensive set of recognition results are generated. A final recognition decision is based upon an input object and its transforms by aggregating the recognition results.