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【速搜问答】检测算法是什么

问答 admin 4周前 (04-10) 24次浏览 已收录 0个评论

汉英对照:
Chinese-English Translation:

检测算法的基本原理就是先通过训练集学习一个分类器,然后在测试图像中以不同scale的窗口滑动扫描整个图像;每次扫描做一下分类,判断一下当前的这个窗口是否为要检测的目标。检测算法的核心是分类,分类的核心一个是用什么特征,一个是用哪种分类器。

The basic principle of the detection algorithm is to learn a classifier through the training set, and then slide scan the whole image with different scale windows in the test image; do a classification each time, and judge whether the current window is the target to be detected. The core of detection algorithm is classification. The core of classification is what features to use and which classifier to use.

在计算机视觉领域,最基本也最经典的一个问题就是目标识别给出一张图像,用 detector 检测出图像中特定的 object(如人脸)。检测算法的基本原理就是先通过训练集学习一个分类器,然后在测试图像中以不同 scale 的窗口滑动扫描整个图像;每次扫描做一下分类,判断一下当前的这个窗口是否为要检测的目标。检测算法的核心是分类,分类的核心一个是用什么特征,一个是用哪种分类器。

In the field of computer vision, the most basic and classic problem is to give an image by object recognition, and use the detector to detect specific objects (such as face) in the image. The basic principle of the detection algorithm is to learn a classifier through the training set, and then slide scan the whole image with different scale windows in the test image; do a classification each time, and judge whether the current window is the target to be detected. The core of detection algorithm is classification. The core of classification is what features to use and which classifier to use.

背景

background

人类所接触的外界信息大约有 80%属于视觉信息。对人类来说,图像以及视频是对客观事物形象与逼真的描述,是人类最主要的信息来源。目标检测与跟踪是计算机视觉研究领域的热门课题,它融合了图像处理、模式识别、人工智能、自动控制等许多领域的前沿技术,在智能化交通系统、智能监控系统、工业检测、航天航空等诸多领域得到了广泛的应用。

About 80% of the external information that human contact belongs to visual information. For human beings, image and video are the vivid description of objective things and the main source of human information. Target detection and tracking is a hot topic in the field of computer vision. It combines the advanced technologies of image processing, pattern recognition, artificial intelligence, automatic control and many other fields. It has been widely used in intelligent transportation system, intelligent monitoring system, industrial detection, aerospace and many other fields.

由于现实世界中的物体(尤其是行人)、场景存在多变性,使其很难用一个同意的方法进行研究。目标检测所遇到的主要问题有:如何准确快速分割目标、尽量减小复杂背景对目标检测的影响以及如何降低因目标尺度、大小和形状发生变化引起的目标检测精确度下降的问题。此外,在目标检测系统中,系统的鲁棒性与实时性这两方面的性能存在矛盾。

Due to the variability of objects (especially pedestrians) and scenes in the real world, it is difficult to use a consensual method to study them. The main problems of target detection are: how to segment the target accurately and quickly, how to minimize the influence of complex background on target detection, and how to reduce the decline of target detection accuracy caused by the change of target scale, size and shape. In addition, in the target detection system, there is a contradiction between the robustness and real-time performance of the system.

研究现状

research status

目标检测的研究主要包括了基于视频图像的目标检测和基于静态图片的目标检测。本文主要讨论基于静态图片的目标检测算法,即在静态图片中检测并定位所设定种类的目标。基于静态图片的目标检测的难点主要在于图片中的目标会因光照、视角以及目标内部等变化而产生变化[}2}。针对以上的难点,国内外学者进行了很多尝试。提出的方法主要分为基于形状轮廓的目标检测算法和基于目标特征的检测方法。

The research of object detection mainly includes object detection based on video image and object detection based on static image. This paper mainly discusses the target detection algorithm based on the static image, that is to detect and locate the set type of target in the static image. The difficulty of object detection based on static image is that the object in the image will change [} 2} because of the change of illumination, angle of view and the inside of the object. In view of the above difficulties, scholars at home and abroad have made many attempts. The proposed methods are mainly divided into shape contour based object detection algorithm and feature-based object detection method.

算法

algorithm

检测算法可以分为六大类,分别是帧间差分法、背景建模法、点检测法、图像分割法、聚类分析法和运动矢量场法。其中,帧差法和背景建模法是最常用、最简单的算法,也在研究中取得了比较好的效果,但是这两种方法有个共同的特点就是只适用于背景静止情况下的运动目标检测。

Detection algorithms can be divided into six categories, namely, inter frame difference method, background modeling method, point detection method, image segmentation method, clustering analysis method and motion vector field method. Among them, frame difference method and background modeling method are the most commonly used and simplest algorithms, and have achieved good results in the research, but the two methods have a common feature that they are only suitable for moving object detection in the case of static background.


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