Object classification method for a collision warning system
    1.
    发明申请
    Object classification method for a collision warning system 审中-公开
    碰撞预警系统的对象分类方法

    公开(公告)号:US20060153459A1

    公开(公告)日:2006-07-13

    申请号:US11032629

    申请日:2005-01-10

    IPC分类号: G06K9/00 G06K9/62

    CPC分类号: G06K9/3241

    摘要: An object classification method for a collision warning system is disclosed. The method includes the steps of capturing a video frame with an imaging device and examining a radar-cued potential object location within the video frame, extracting orthogonal moment features from the potential object location, extracting Gabor filtered features from the potential object location, and classifying the potential object location into one of a first type of image or a second type of image in view of the extracted orthogonal moment features and the Gabor filtered features.

    摘要翻译: 公开了一种用于碰撞预警系统的物体分类方法。 该方法包括以下步骤:利用成像设备捕获视频帧并检查视频帧内的雷达提示潜在对象位置,从潜在对象位置提取正交时刻特征,从潜在对象位置提取Gabor滤波特征,以及分类 鉴于所提取的正交矩特征和Gabor滤波特征,将潜在对象位置转换成第一类型的图像或第二类型的图像之一。

    Object classification method utilizing wavelet signatures of a monocular video image
    2.
    发明申请
    Object classification method utilizing wavelet signatures of a monocular video image 审中-公开
    利用单眼视频图像小波特征的对象分类方法

    公开(公告)号:US20060088219A1

    公开(公告)日:2006-04-27

    申请号:US10973584

    申请日:2004-10-26

    IPC分类号: G06K9/62 E05F15/00

    摘要: A stream of images including an area occupied by at least one object are processed to extract wavelet coefficients, and the extracted coefficients are represented as wavelet signatures that are less susceptible to misclassification due to noise and extraneous object features. Representing the wavelet coefficients as wavelet signatures involves sorting the coefficients by magnitude, setting a coefficient threshold based on the distribution of coefficient magnitudes, truncating coefficients whose magnitude is less than the threshold, and quantizing the remaining coefficients.

    摘要翻译: 处理包括至少一个对象占据的区域的图像流以提取小波系数,并且所提取的系数被表示为由于噪声和无关对象特征而不易于错误分类的小波特征。 将小波系数表示为小波特征涉及对系数进行大小分级,基于系数幅度的分布,幅度小于阈值的截断系数,以及量化剩余系数来设定系数阈值。

    Identification and labeling of beam images of a structured beam matrix
    3.
    发明申请
    Identification and labeling of beam images of a structured beam matrix 有权
    结构束矩阵的束图像的识别和标记

    公开(公告)号:US20050185194A1

    公开(公告)日:2005-08-25

    申请号:US10784648

    申请日:2004-02-23

    IPC分类号: G01B11/25 G06T5/00 G01B11/24

    摘要: A technique for identifying beam images of a beam matrix includes a number of steps. Initially, a plurality of light beams of a beam matrix, which are arranged in rows and columns, are received after reflection from a surface of a target. Next, a reference light beam is located in the beam matrix. Then, a row pivot beam is located in the beam matrix based on the reference beam. Next, remaining reference row beams of a reference row that includes the row pivot beam and the reference beam are located. Then, a column pivot beam in the beam matrix is located based on the reference beam. Next, remaining reference column beams of a reference column that includes the column pivot beam and the reference beam are located. Finally, remaining ones of the light beams in the beam matrix are located.

    摘要翻译: 用于识别波束矩阵的波束图像的技术包括多个步骤。 最初,从目标表面反射之后,接收以行和列排列的多个束矩阵的光束。 接下来,参考光束位于光束矩阵中。 然后,基于参考光束,行摆动光束位于光束矩阵中。 接下来,定位包括行摆动光束和参考光束的参考行的剩余参考行光束。 然后,基于参考光束定位在光束矩阵中的列枢转光束。 接下来,定位包括列枢转光束和参考光束的参考列的剩余参考列光束。 最后,光束矩阵中剩余的一束光束被定位。

    Method and apparatus for recognizing the position of an occupant in a vehicle
    4.
    发明申请
    Method and apparatus for recognizing the position of an occupant in a vehicle 审中-公开
    用于识别乘员在车辆中的位置的方法和装置

    公开(公告)号:US20050201591A1

    公开(公告)日:2005-09-15

    申请号:US10797411

    申请日:2004-03-10

    IPC分类号: G06K9/00 G06K9/62

    摘要: A method of object detection includes receiving images of an area occupied by at least one object. Image features including wavelet features are extracted from the images. Classification is performed on the image features as a group in at least one common classification algorithm to produce object class confidence data.

    摘要翻译: 一种物体检测方法包括接收由至少一个物体占据的区域的图像。 从图像中提取包括小波特征的图像特征。 在至少一种常见分类算法中,以图像特征作为一组进行分类,以产生对象类置信度数据。