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公开(公告)号：US20160148071A1
公开(公告)日：2016-05-26
申请号：US14551942
申请日：2014-11-24
Applicant: TEXAS INSTRUMENTS INCORPORATED
Inventor： Kumar Arrakutti Desappan , Manu Mathew , Pramod Kumar Swami
CPC classification number: G06K9/4647 , G06K9/4652 , G06K9/6212
Abstract: An object detection system and a method of detecting an object in an image are disclosed. In an embodiment, a method for detecting the object includes computing one or more feature planes of one or more types for each image pixel of the image. A plurality of cells is defined in the image, where each cell includes first through nth number of pixels, and starting locations of each cell in the image in horizontal and vertical directions are integral multiples of predefined horizontal and vertical step sizes, respectively. One or more feature plane summations of one or more types are computed for each cell. A feature vector is determined for an image portion of the image based on a set of feature plane summations, and the feature vector is compared with a corresponding object classifier to detect a presence of the corresponding object in the image portion of the image.
Abstract translation: 公开了一种物体检测系统和检测图像中物体的方法。 在一个实施例中，用于检测对象的方法包括为图像的每个图像像素计算一个或多个类型的一个或多个特征面。 在图像中定义多个单元，其中每个单元包括第一至第n个像素数，并且图像中每个单元在水平和垂直方向上的起始位置分别是预定水平和垂直步长的整数倍。 为每个单元计算一个或多个类型的一个或多个特征平面求和。 基于特征平面求和的集合来确定图像的图像部分的特征向量，并且将特征向量与对应的对象分类器进行比较，以检测图像的图像部分中相应对象的存在。
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公开(公告)号：US09508018B2
公开(公告)日：2016-11-29
申请号：US14551942
申请日：2014-11-24
Applicant: TEXAS INSTRUMENTS INCORPORATED
Inventor： Kumar Arrakutti Desappan , Manu Mathew , Pramod Kumar Swami
CPC classification number: G06K9/4647 , G06K9/4652 , G06K9/6212
Abstract: An object detection system and a method of detecting an object in an image are disclosed. In an embodiment, a method for detecting the object includes computing one or more feature planes of one or more types for each image pixel of the image. A plurality of cells is defined in the image, where each cell includes first through nth number of pixels, and starting locations of each cell in the image in horizontal and vertical directions are integral multiples of predefined horizontal and vertical step sizes, respectively. One or more feature plane summations of one or more types are computed for each cell. A feature vector is determined for an image portion of the image based on a set of feature plane summations, and the feature vector is compared with a corresponding object classifier to detect a presence of the corresponding object in the image portion of the image.
Abstract translation: 公开了一种物体检测系统和检测图像中物体的方法。 在一个实施例中，用于检测对象的方法包括为图像的每个图像像素计算一个或多个类型的一个或多个特征面。 在图像中定义多个单元，其中每个单元包括第一至第n个像素数，并且图像中每个单元在水平和垂直方向上的起始位置分别是预定水平和垂直步长的整数倍。 为每个单元计算一个或多个类型的一个或多个特征平面求和。 基于特征平面求和的集合来确定图像的图像部分的特征向量，并且将特征向量与对应的对象分类器进行比较，以检测图像的图像部分中相应对象的存在。
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