Object detection apparatus and method
    1.
    发明申请
    Object detection apparatus and method 审中-公开
    物体检测装置及方法

    公开(公告)号:US20050105771A1

    公开(公告)日:2005-05-19

    申请号:US10930566

    申请日:2004-08-30

    摘要: The object detection apparatus according to the invention detects an object based on input images that are captured sequentially in time in a moving unit. The apparatus generates an action command to be sent to the moving unit, calculates flow information for each local area in the input image, and estimates an action of the moving unit based on the flow information. The apparatus calculates a difference between the estimated action and the action command and then determines a specific local area as a figure area when such difference in association with that specific local area exhibits an error larger than a predetermined value. The apparatus determines presence/absence of an object in the figure area.

    摘要翻译: 根据本发明的对象检测装置基于在移动单元中及时地顺序地捕获的输入图像来检测对象。 该装置生成要发送到移动单元的动作命令,计算输入图像中的每个局部区域的流量信息,并基于流信息来估计移动单元的动作。 该装置计算估计动作和动作命令之间的差,然后当与该特定局部区域相关联的这种差异表现出大于预定值的误差时,将特定局部区域确定为图形区域。 该装置确定图形区域中的对象的存在/不存在。

    Image-based object detection apparatus and method
    2.
    发明申请
    Image-based object detection apparatus and method 失效
    基于图像的物体检测装置及方法

    公开(公告)号:US20050248654A1

    公开(公告)日:2005-11-10

    申请号:US10624786

    申请日:2003-07-21

    摘要: An object detection apparatus and method capable of detecting objects based on visual images captured by a self-moving unit. A sequential images output section makes a train of a first input image and a second input image sequential to the first input image and outputs said train. A local area image processor calculates local flows based on said first input image and said second input image. An inertia information acquiring section measures self-motion of the unit to calculate inertia information thereof. A global area image processor uses said inertia information to estimate global flow, which is a motion field of the entire view associated to the self-motion, using said global flow and said first input image and creates a predictive image of said second input image. The global area image processor then calculates differential image data, which is a difference between said predictive image and said second input image. A figure-ground segregation section uses said differential image data to refine said local flows and compares the refined local flows with a predetermined threshold value to extract a figure candidate area, which is the area having a high probability of an object existing in the input image. An object presence/absence determination section determines presence/absence of objects in said figure candidate area.

    摘要翻译: 一种能够基于由自动移动单元捕获的视觉图像来检测物体的物体检测装置和方法。 顺序图像输出部分构成与第一输入图像顺序的第一输入图像和第二输入图像的列,并输出所述列。 局部区域图像处理器基于所述第一输入图像和所述第二输入图像来计算局部流。 惯性信息获取部分测量该单元的自动运动以计算其惯性信息。 全局区域图像处理器使用所述惯性信息来估计使用所述全局流和所述第一输入图像并创建所述第二输入图像的预测图像的全自动运动的全局流动,其是与自动运动相关联的整个视图的运动场。 然后,全局区域图像处理器计算作为所述预测图像和所述第二输入图像之间的差的差分图像数据。 图形分离部分使用所述差分图像数据来细化所述本地流并将精细局部流与预定阈值进行比较,以提取图形候选区域,其是存在于输入图像中的对象的概率高的区域 。 对象存在/不存在确定部分确定所述图形候选区域中的对象的存在/不存在。

    Apparatus, program and method for detecting both stationary objects and moving objects in an image using optical flow
    3.
    发明授权
    Apparatus, program and method for detecting both stationary objects and moving objects in an image using optical flow 有权
    用于使用光流检测图像中的静止物体和移动物体的装置,程序和方法

    公开(公告)号:US07062071B2

    公开(公告)日:2006-06-13

    申请号:US10322307

    申请日:2002-12-17

    IPC分类号: G06K9/00

    摘要: An object detection apparatus is provided for detecting both stationary objects and moving objects accurately from an image captured from a moving mobile unit.The object detection apparatus of the present invention applies Gabor filter to two or more input images captured by an imaging device such as CCD camera mounted on a mobile unit, and calculates optical flow of local areas in the input images. Then the object detection apparatus closely removes optical flow produced by motion of the mobile unit by estimating optical flow produced from background of the input images. In other words, the object detection apparatus clarifies the area where object is not present (“ground”) in the input images. By removing such “ground” part, the area where objects seems to be present (“feature”) is extracted from the input images. Finally, the object detection apparatus determines whether objects are present or not using flow information of the extracted “feature” part.

    摘要翻译: 提供一种物体检测装置,用于从移动的移动单元捕获的图像中精确地检测静止物体和移动物体。 本发明的对象检测装置将Gabor滤波器应用于由安装在移动单元上的CCD摄像机等摄像装置拍摄的两个以上的输入图像,并计算输入图像中局部区域的光流。 然后,物体检测装置通过估计从输入图像的背景产生的光流来紧密地去除由移动单元的运动产生的光流。 换句话说,对象检测装置说明输入图像中不存在对象(“接地”)的区域。 通过移除这样的“地面”部分,从输入图像中提取对象似乎存在的区域(“特征”)。 最后,对象检测装置使用提取的“特征”部分的流信息来确定对象是否存在。

    Image-based object detection apparatus and method
    4.
    发明授权
    Image-based object detection apparatus and method 失效
    基于图像的物体检测装置及方法

    公开(公告)号:US07295684B2

    公开(公告)日:2007-11-13

    申请号:US10624786

    申请日:2003-07-21

    IPC分类号: G06K9/00

    摘要: An object detection apparatus and method capable of detecting objects based on visual images captured by a self-moving unit. A sequential images output section makes a train of a first input image and a second input image sequential to the first input image and outputs said train. A local area image processor calculates local flows based on said first input image and said second input image. An inertia information acquiring section measures self-motion of the unit to calculate inertia information thereof. A global area image processor uses said inertia information to estimate global flow, which is a motion field of the entire view associated to the self-motion, using said global flow and said first input image and creates a predictive image of said second input image. The global area image processor then calculates differential image data, which is a difference between said predictive image and said second input image. A figure-ground segregation section uses said differential image data to refine said local flows and compares the refined local flows with a predetermined threshold value to extract a figure candidate area, which is the area having a high probability of an object existing in the input image. An object presence/absence determination section determines presence/absence of objects in said figure candidate area.

    摘要翻译: 一种能够基于由自动移动单元捕获的视觉图像来检测物体的物体检测装置和方法。 顺序图像输出部分构成与第一输入图像顺序的第一输入图像和第二输入图像的列,并输出所述列。 局部区域图像处理器基于所述第一输入图像和所述第二输入图像来计算局部流。 惯性信息获取部分测量该单元的自动运动以计算其惯性信息。 全局区域图像处理器使用所述惯性信息来估计使用所述全局流和所述第一输入图像并创建所述第二输入图像的预测图像的全自动运动的全局流动,其是与自动运动相关联的整个视图的运动场。 然后,全局区域图像处理器计算作为所述预测图像和所述第二输入图像之间的差的差分图像数据。 图形分离部分使用所述差分图像数据来细化所述本地流并将精细局部流与预定阈值进行比较,以提取图形候选区域,其是存在于输入图像中的对象的概率高的区域 。 对象存在/不存在确定部分确定所述图形候选区域中的对象的存在/不存在。

    Image recognizing apparatus and method
    5.
    发明授权
    Image recognizing apparatus and method 失效
    图像识别装置及方法

    公开(公告)号:US07221797B2

    公开(公告)日:2007-05-22

    申请号:US10133114

    申请日:2002-04-26

    IPC分类号: G06K9/46

    CPC分类号: G06K9/00335 G05D1/0253

    摘要: An image recognizing apparatus and method is provided for recognizing behavior of a mobile unit accurately with an image of external environment acquired during the mobile unit is moving.Behavior command output block 12 outputs behavior commands to cause the mobile unit 32 move. Local feature extraction block 16 extracts features of local areas of the image from the image of external environment acquired on the mobile unit 32 when the behavior command is output. Global feature extraction block 18 extracts feature of global area of the image using the features of local areas. Learning block 20 calculates probability models for recognizing behavior given to the mobile unit 32 based on the feature of global area of the image. After learning is finished, behavior of the mobile unit 32 may be recognized rapidly and accurately by applying the probability models to an image of external environment acquired in mobile unit 32 afresh.

    摘要翻译: 提供一种图像识别装置和方法,用于在移动单元移动期间获取的外部环境的图像精确地识别移动单元的行为。 行为命令输出块12输出行为命令以使移动单元32移动。 局部特征提取块16当输出行为命令时,从移动单元32上获取的外部环境的图像中提取图像的局部区域的特征。 全局特征提取块18使用局部区域的特征提取图像的全局区域的特征。 学习块20基于图像的全局区域的特征来计算用于识别给予移动单元32的行为的概率模型。 在完成学习之后,通过将概率模型应用于移动单元32中获取的外部环境的图像,可以快速且准确地识别移动单元32的行为。

    Behavior control apparatus and method
    6.
    发明授权
    Behavior control apparatus and method 有权
    行为控制装置及方法

    公开(公告)号:US07054724B2

    公开(公告)日:2006-05-30

    申请号:US10484147

    申请日:2002-07-16

    IPC分类号: G05D1/00

    CPC分类号: G05D1/0088

    摘要: The invention relates to a behavior control apparatus and method for autonomously controlling a mobile unit based on visual information in practical application without the needs of a greatdeal of preparation or computational cost and limiting the type of target object. According to one aspect of the invention, a method for controlling behavior of a mobile unit using behavior command is provided. First, sensory inputs are captured and then the motion of the mobile unit is estimated. The portion which includes a target object to be target for behavior of the mobile unit is segregated from the sensory inputs. The target objects extracted from the segregated portion and the location of the target object is acquired. Finally, the mobile unit is controlled based on the location of target object.

    摘要翻译: 本发明涉及一种用于在实际应用中基于视觉信息自主控制移动单元的行为控制装置和方法,而不需要大量准备或计算成本,并限制目标对象的类型。 根据本发明的一个方面,提供了一种使用行为命令来控制移动单元的行为的方法。 首先,捕获感觉输入,然后估计移动单元的运动。 包含目标对象的部分,其目标是针对移动单元的行为与感官输入隔离。 获取从分离部分提取的目标对象和目标对象的位置。 最后,根据目标对象的位置来控制移动单元。

    System and method for face recognition
    7.
    发明授权
    System and method for face recognition 有权
    面部识别系统和方法

    公开(公告)号:US07783082B2

    公开(公告)日:2010-08-24

    申请号:US10561256

    申请日:2004-06-30

    IPC分类号: G06K9/00

    摘要: A face recognition system includes a component learning/extraction module, component classifier training module, knowledge base for component classification (KBCC), component extraction module (CEM), object identification training module (OITM), knowledge base for face identification (KBFI), and object identification module (OIM). The CEM receives image data of faces at various viewpoints and extracts outputs of classification of the component data, using the results of classifier training of the component data, stored in the KBCC. The OITM receives the outputs of classification of the component data and determines indicator component for each person by Bayesian estimation so that posterior probability of a predetermined attention class is maximized under the outputs of classification of the component data at various viewpoints. The KBFI stores indicator components for the individuals. The OIM receives the outputs of classification of the component data and identifies faces using the indicator components stored in the KBFI.

    摘要翻译: 面部识别系统包括组件学习/提取模块,组件分类器训练模块,组件分类知识库(KBCC),组件提取模块(CEM),对象识别训练模块(OITM),面部识别知识库(KBFI) 和对象识别模块(OIM)。 CEM在各种视点接收面部的图像数据,利用存储在KBCC中的分量数据的分类器训练结果,提取分量数据的分类输出。 OITM接收分量数据的分类输出,并通过贝叶斯估计确定每个人的指标分量,使得在各种视点下,在分量数据的分类输出下,使预定注意力级别的后验概率最大化。 KBFI存储个人的指示器组件。 OIM接收组件数据分类的输出,并使用KBFI中存储的指示器组件识别面。

    System and method for face recognition
    8.
    发明申请
    System and method for face recognition 有权
    面部识别系统和方法

    公开(公告)号:US20060280341A1

    公开(公告)日:2006-12-14

    申请号:US10561256

    申请日:2004-06-30

    IPC分类号: G06K9/00

    摘要: A production device and method which produce a multiple-system film having metal components such as TiAlN greatly different in melting point by a melting-evaporation type ion plating method that provides a high material utilization efficiency and a good film quality. Power needed to evaporate a material (4) is first supplied, and then power gradually increased over the initail power is repeatedly supplied until a needed maximum power is reached. Concurrently, a plasma control is performed for converging plasma (7) onto an initial area needed to evaporate the material, and then a plasma control is performed for continuously and sequentially moving/expanding plasma from the initial plasma area up to a maximum plasma area to thereby gradually melt the non-melted portion of the material.

    Agent learning apparatus, method and program
    9.
    发明申请
    Agent learning apparatus, method and program 审中-公开
    代理学习装置,方法和程序

    公开(公告)号:US20060155660A1

    公开(公告)日:2006-07-13

    申请号:US10468316

    申请日:2002-02-04

    IPC分类号: G06E1/00

    CPC分类号: G05B13/0265 G05B13/027

    摘要: An agent learning apparatus comprises a sensor (301) for acquiring a sense input, an action controller (307) for creating an action output in response to the sense input and giving the action output to a controlled object, an action state evaluator (303) for evaluating the behavior of the controlled object, a selective attention mechanism (304) for storing the action output and the sense input corresponding to the action output in one of the columns according to the evaluation, calculating a probability model from the action outputs stored in the columns, and outputting, as a learning result, the action output related to a newly given sense input in the column where the highest confidence obtained by applying the newly given sense input to the probability model is stored. By thus learning, the selective attention mechanism (304) obtains a probability relationship between the sense input and the column. An action output is calculated on the basis of the column evaluated as a stable column. As a result, the dispersion of the action output is quickly minimized, and thereby the controlled object can be stabilized.

    摘要翻译: 代理学习装置包括用于获取感测输入的传感器(301),用于响应于感测输入创建动作输出并将动作输出给受控对象的动作控制器(307),动作状态评估器(303) 用于评估受控对象的行为的选择性注意机制(304),用于根据评估将动作输出和对应于动作输出的感测输入存储在一列中的选择性注意机制(304),从存储在 并且作为学习结果输出与通过将新给定的感测输入应用于概率模型获得的最高置信度的列中的新给定的感测输入相关的动作输出被存储。 通过这样学习,选择性注意机制(304)获得感知输入和列之间的概率关系。 基于作为稳定列计算的列计算动作输出。 结果,动作输出的分散被快速地最小化,从而可以使受控对象稳定。

    Trajectory planning method, trajectory planning system and robot
    10.
    发明授权
    Trajectory planning method, trajectory planning system and robot 有权
    轨迹规划方法,轨迹规划系统和机器人

    公开(公告)号:US08774968B2

    公开(公告)日:2014-07-08

    申请号:US13004517

    申请日:2011-01-11

    IPC分类号: G05B19/04

    CPC分类号: B25J9/1666 G05B2219/40446

    摘要: A trajectory planning system obtains a trajectory for controlling a state of an object toward a goal state. The system includes a search tree generating section which registers a state of the object as a root of a search tree in a state space, registers a next state of the object after a lapse of a predetermined time interval obtained through dynamical relationships during the time interval as a branch of the search tree in the state space. The system further includes a known-state registration tree storing section which stores a known-state registration tree and a known-state registration tree generating section which determines a cell to which the next state belongs among a plurality of cells previously prepared by segmenting the state space, determines whether or not a state which belongs to the cell has already been registered as a branch of the known-state registration tree, discards the next state when a state which belongs to the cell has been registered, and registers the next step as a branch of the known-state registration tree when a state which belongs to the cell has not been registered. The system further includes a trajectory generating section which selects a state whose distance to the goal state is minimum among states registered as branches of the known-state registration tree and obtains a trajectory using a sequence of states in a backward direction from the state toward the root of the known-state registration tree.

    摘要翻译: 轨迹规划系统获得用于控制物体朝向目标状态的状态的轨迹。 该系统包括搜索树生成部分,其将对象的状态作为搜索树的根登记在状态空间中,在经过在时间间隔期间通过动态关系获得的预定时间间隔之后登记对象的下一状态 作为状态空间中搜索树的分支。 该系统还包括已知状态注册树存储部分,其存储已知状态注册树和已知状态注册树生成部分,该已知状态注册树生成部分通过分割状态来确定先前准备的多个小区中下一状态所属的小区 空间,确定属于小区的状态是否已经被注册为已知状态注册树的分支,当属于小区的状态已被注册时,丢弃下一状态,并将下一步骤注册为 当属于小区的状态尚未被注册时,已知状态注册树的分支。 该系统还包括:轨迹生成部,其选择在已知状态登记树的分支中登记为状态的目标状态的距离为最小的状态,并使用从状态朝向状态的向后方向的状态序列获取轨迹 已知状态注册树的根。