会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 23. 发明授权
    • Pose to device mapping
    • 姿态到设备映射
    • US09591118B2
    • 2017-03-07
    • US12347999
    • 2009-01-01
    • David L. GraumannGiuseppe RaffaLama Nachman
    • David L. GraumannGiuseppe RaffaLama Nachman
    • G06F3/16H04M1/725G06F3/01H04M1/60
    • H04M1/7253G06F3/011G06F3/167H04M1/6066H04M2250/02H04M2250/12
    • Embodiments may comprise logic such as hardware and/or code to map content of a device such as a mobile device, a laptop, a desktop, or a server, to a two dimensional field or table and map user poses or movements to the coordinates within the table to offer quick access to the content by a user. Many embodiments, for example, utilize three wireless peripherals such as a watch, ring, and headset connected to a mobile Internet device (MID) comprising an audible user interface and an auditory mapper to access to the content. The audible user interface may communicatively couple with the peripherals to receive pose data that describes the motion or movements associated with one or more of the peripherals and to provide feedback such as audible items and, in some embodiments, other feedback.
    • 实施例可以包括诸如硬件和/或代码之类的逻辑,以将诸如移动设备,膝上型计算机,桌面或服务器之类的设备的内容映射到二维场或表,并将用户姿态或运动映射到坐标内 该表提供用户快速访问内容。 例如,许多实施例利用连接到包括可听用户界面和听觉映射器的移动因特网设备(MID)的三个无线外围设备,例如手表,环和耳机来访问内容。 可听用户界面可以与外围设备通信地耦合以接收描述与一个或多个外围设备相关联的运动或运动的姿势数据,并提供诸如可听项目之类的反馈,并且在一些实施例中提供其他反馈。
    • 26. 发明申请
    • ADJUSTMENT OF TEMPORAL ACOUSTICAL CHARACTERISTICS
    • 时间声学特性的调整
    • US20100169075A1
    • 2010-07-01
    • US12347977
    • 2008-12-31
    • Giuseppe RaffaLama NachmanDavid L. GraumannMichael E. Deisher
    • Giuseppe RaffaLama NachmanDavid L. GraumannMichael E. Deisher
    • G06F17/27G10L13/08
    • G06F17/2775G10L13/00
    • Embodiments may be a standalone module or part of mobile devices, desktop computers, servers, stereo systems, or any other systems that might benefit from condensed audio presentations of item structures such as lists or tables. Embodiments may comprise logic such as hardware and/or code to adjust the temporal characteristics of items comprising words. The items maybe included in a structure such as a text listing or table, an audio listing or table, or a combination thereof, or may be individual words or phrases. For instance, embodiments may comprise a keyword extractor to extract keywords from the items and an abbreviations generator to generate abbreviations based upon the keywords. Further embodiments may comprise a text-to-speech generator to generate audible items based upon the abbreviations to render to a user while traversing the item structure.
    • 实施例可以是独立模块或移动设备,台式计算机,服务器,立体声系统或可能受益于诸如列表或表的项目结构的聚合音频呈现的任何其他系统的独立模块或部分。 实施例可以包括诸如硬件和/或代码的逻辑,以调整包括单词的项目的时间特征。 项目可以包括在诸如文本列表或表格,音频列表或表格或其组合的结构中,或者可以是单独的单词或短语。 例如,实施例可以包括从项目中提取关键词的关键字提取器和缩写生成器,以基于关键字生成缩写。 另外的实施例可以包括文本到语音生成器,以便在遍历项目结构的同时基于缩写来生成可听见的项目以呈现给用户。
    • 27. 发明授权
    • Efficient gesture processing
    • 高效的手势处理
    • US09535506B2
    • 2017-01-03
    • US14205210
    • 2014-03-11
    • Giuseppe RaffaLama NachmanJinwon Lee
    • Giuseppe RaffaLama NachmanJinwon Lee
    • G06F1/16G06F3/01G06F3/0346
    • G06F3/017G01C19/00G01P15/18G06F1/1694G06F3/0346H04M2250/12
    • Embodiments of the invention describe a system to efficiently execute gesture recognition algorithms. Embodiments of the invention describe a power efficient staged gesture recognition pipeline including multimodal interaction detection, context based optimized recognition, and context based optimized training and continuous learning. Embodiments of the invention further describe a system to accommodate many types of algorithms depending on the type of gesture that is needed in any particular situation. Examples of recognition algorithms include but are not limited to, HMM for complex dynamic gestures (e.g. write a number in the air), Decision Trees (DT) for static poses, peak detection for coarse shake/whack gestures or inertial methods (INS) for pitch/roll detection.
    • 本发明的实施例描述了一种有效执行手势识别算法的系统。 本发明的实施例描述了一种功率效率分级手势识别流水线,其包括多模式交互检测,基于上下文的优化识别和基于上下文的优化训练和连续学习。 本发明的实施例进一步描述了根据在任何特定情况下需要的手势类型来适应许多类型的算法的系统。 识别算法的示例包括但不限于用于复杂动态手势的HMM(例如在空中编写一个数字),用于静态姿势的决策树(DT),用于粗略摇动/打击手势的峰值检测或惯性方法(INS),用于 俯仰/滚动检测。
    • 30. 发明申请
    • EFFICIENT GESTURE PROCESSING
    • 高效的加工
    • US20120016641A1
    • 2012-01-19
    • US12835079
    • 2010-07-13
    • Giuseppe RaffaLama NachmanJinwon Lee
    • Giuseppe RaffaLama NachmanJinwon Lee
    • G06F17/10G06F15/00G01P15/00
    • G06F3/017G01C19/00G01P15/18G06F1/1694G06F3/0346H04M2250/12
    • Embodiments of the invention describe a system to efficiently execute gesture recognition algorithms. Embodiments of the invention describe a power efficient staged gesture recognition pipeline including multimodal interaction detection, context based optimized recognition, and context based optimized training and continuous learning. Embodiments of the invention further describe a system to accommodate many types of algorithms depending on the type of gesture that is needed in any particular situation. Examples of recognition algorithms include but are not limited to, HMM for complex dynamic gestures (e.g. write a number in the air), Decision Trees (DT) for static poses, peak detection for coarse shake/whack gestures or inertial methods (INS) for pitch/roll detection.
    • 本发明的实施例描述了一种有效执行手势识别算法的系统。 本发明的实施例描述了一种功率效率分级手势识别流水线,其包括多模式交互检测,基于上下文的优化识别和基于上下文的优化训练和连续学习。 本发明的实施例进一步描述了根据在任何特定情况下需要的手势类型来适应许多类型的算法的系统。 识别算法的示例包括但不限于用于复杂动态手势的HMM(例如在空中编写一个数字),用于静态姿势的决策树(DT),用于粗略摇动/打击手势的峰值检测或惯性方法(INS),用于 俯仰/滚动检测。