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1. 发明申请

US20120214594A1 MOTION RECOGNITION 有权
标题翻译：运动识别
公开(公告)号：US20120214594A1
公开(公告)日：2012-08-23
申请号：US13030154
申请日：2011-02-18
申请人： Darko Kirovski , Michail Raptis
发明人： Darko Kirovski , Michail Raptis
IPC分类号： A63F9/24
CPC分类号： A63F13/42 , A63F13/213 , A63F2300/1093 , A63F2300/6045 , A63F2300/6607 , G06K9/00208 , G06K9/00342 , G06K9/00355 , G06K9/2018
摘要： Human body motion is represented by a skeletal model derived from image data of a user. Skeletal model data may be used to perform motion recognition and/or similarity analysis of body motion. An example method of motion recognition includes receiving skeletal motion data representative of a user data motion feature from a capture device relating to a position of a user within a scene. A cross-correlation of the received skeletal motion data relative to a plurality of prototype motion features from a prototype motion feature database is determined. Likelihoods that the skeletal motion data corresponds to each of the plurality of prototype motion features are ranked. The likelihoods are determined using the cross-correlation. A classifying operation is performed on a subset of the plurality of prototype motion features. The subset of the plurality of prototype motion features is chosen because its members have the relatively highest likelihoods of corresponding to the skeletal motion data.
摘要翻译：人体运动由来自用户的图像数据的骨骼模型表示。骨骼模型数据可用于执行身体运动的运动识别和/或相似性分析。运动识别的示例性方法包括：从与捕获装置相关的用户在场景中的位置的表示用户数据运动特征的骨架运动数据。确定从原型运动特征数据库接收到的骨架运动数据相对于多个原型运动特征的互相关。骨骼运动数据对应于多个原型运动特征中的每一个的可能性被排序。使用互相关确定似然性。对多个原型运动特征的子集执行分类操作。选择多个原型运动特征的子集，因为其成员具有对应于骨骼运动数据的相对较高的可能性。

2. 发明授权

US08761437B2 Motion recognition 有权
标题翻译：运动识别
公开(公告)号：US08761437B2
公开(公告)日：2014-06-24
申请号：US13030154
申请日：2011-02-18
申请人： Darko Kirovski , Michail Raptis
发明人： Darko Kirovski , Michail Raptis
IPC分类号： G06K9/00
CPC分类号： A63F13/42 , A63F13/213 , A63F2300/1093 , A63F2300/6045 , A63F2300/6607 , G06K9/00208 , G06K9/00342 , G06K9/00355 , G06K9/2018
摘要： Human body motion is represented by a skeletal model derived from image data of a user. Skeletal model data may be used to perform motion recognition and/or similarity analysis of body motion. An example method of motion recognition includes receiving skeletal motion data representative of a user data motion feature from a capture device relating to a position of a user within a scene. A cross-correlation of the received skeletal motion data relative to a plurality of prototype motion features from a prototype motion feature database is determined. Likelihoods that the skeletal motion data corresponds to each of the plurality of prototype motion features are ranked. The likelihoods are determined using the cross-correlation. A classifying operation is performed on a subset of the plurality of prototype motion features. The subset of the plurality of prototype motion features is chosen because its members have the relatively highest likelihoods of corresponding to the skeletal motion data.
摘要翻译：人体运动由来自用户的图像数据的骨骼模型表示。骨骼模型数据可用于执行身体运动的运动识别和/或相似性分析。运动识别的示例性方法包括：从与捕获装置相关的用户在场景中的位置的表示用户数据运动特征的骨架运动数据。确定从原型运动特征数据库接收到的骨架运动数据相对于多个原型运动特征的互相关。骨骼运动数据对应于多个原型运动特征中的每一个的可能性被排序。使用互相关确定似然性。对多个原型运动特征的子集执行分类操作。选择多个原型运动特征的子集，因为其成员具有对应于骨骼运动数据的相对较高的可能性。

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