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    • 1. 发明申请
    • DETECTING DEVICE OF SPECIAL SHOT OBJECT AND LEARNING DEVICE AND METHOD THEREOF
    • 检测特殊拍摄对象和学习装置的装置及其方法
    • US20100202681A1
    • 2010-08-12
    • US12602635
    • 2008-05-30
    • Haizhou AiYuan LiShihong LaoTakayoshi Yamashita
    • Haizhou AiYuan LiShihong LaoTakayoshi Yamashita
    • G06K9/62
    • G06K9/6257G06K9/00248
    • The invention discloses a detecting device for specific subjects and a learning device and method thereof. The detecting device for specific subjects includes an input unit, one or more strong classifying units, a storage unit and a judging unit, wherein the input unit is used for inputting images to be detected; the strong classifying units are used for carrying out strong classification to the image, each strong classifying unit includes one or more weak classifying units, and the weak classifying unit carries out weak classification to the image with a weak classifying template; the storage unit stores the weak classifying template used by the weak classifying unit; and the judging unit judges whether or not the image contains specific subjects according to the classification result of the strong classifying unit. The detecting device for specific subjects also includes an incremental sample input unit and a learning unit, wherein the incremental sample input unit is used for inputting data for incremental learning, namely for inputting an incremental learning sample, which is data undetected and wrongly detected by the detecting device or other detecting devices for specific subjects; the learning unit is used for updating the weak classifying template stored in the storage unit according to the incremental learning sample inputted by the incremental sample input unit.
    • 本发明公开了一种特定对象的检测装置及其学习装置及其方法。 用于特定对象的检测装置包括输入单元,一个或多个强分类单元,存储单元和判断单元,其中输入单元用于输入要检测的图像; 强分类单位用于对图像进行强分类,每个强分类单位包括一个或多个弱分类单位,弱分类单位用弱分类模板对图像进行弱分类; 存储单元存储由弱分类单元使用的弱分类模板; 并且判断单元根据强分类单元的分类结果判断图像是否包含特定对象。 用于特定主体的检测装置还包括增量采样输入单元和学习单元,其中增量采样输入单元用于输入用于增量学习的数据,即用于输入增量学习样本,该增量学习样本是未被检测到并被错误检测的数据 用于特定对象的检测装置或其他检测装置; 学习单元用于根据由增量抽样输入单元输入的递增学习样本来更新存储在存储单元中的弱分类模板。
    • 2. 发明授权
    • Tracking method and device adopting a series of observation models with different life spans
    • 跟踪方法和装置采用不同寿命的一系列观察模型
    • US08548195B2
    • 2013-10-01
    • US12664588
    • 2008-06-13
    • Haizhou AiYuan LiShihong LaoTakayoshi Yamashita
    • Haizhou AiYuan LiShihong LaoTakayoshi Yamashita
    • G06K9/00
    • G06T7/277G06T2207/10016G06T2207/30201
    • The present invention relates to a tracking method and a tracking device adopting multiple observation models with different life spans. The tracking method is suitable for tracking an object in a low frame rate video or with abrupt motion, and uses three observation models with different life spans to track and detect a specific subject in frame images of a video sequence. An observation model I performs online learning with one frame image prior to the current image, an observation model II performs online learning with five frames prior to the current image, and an observation model III is offline trained. The three observation models are combined by a cascade particle filter so that the specific subject in the low frame rate video or the object with abrupt motion can be tracked quickly and accurately.
    • 本发明涉及采用具有不同寿命的多个观察模型的跟踪方法和跟踪装置。 跟踪方法适用于跟踪低帧率视频或突然运动的对象,并且使用具有不同寿命的三个观察模型来跟踪和检测视频序列的帧图像中的特定主体。 观察模型I在当前图像之前用一帧图像执行在线学习,观察模型II在当前图像之前用五帧执行在线学习,并且观察模型III被离线训练。 三个观察模型通过级联粒子滤波器组合,使得低帧率视频中的特定对象或具有突然运动的对象能够被快速准确地跟踪。