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Pedestrian Detection Method Based on Weighted Component Model and Selective Search Segmentation

A component model and pedestrian detection technology, which is applied in the field of pedestrian detection, can solve the problems of the detection rate drop of the deformable component model and the limited visibility of pedestrian outlines, etc.

Active Publication Date: 2019-06-28
河北燕大燕软信息系统有限公司
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Problems solved by technology

However, in crowded scenes, due to the existence of partial occlusion, the visibility of pedestrian silhouettes is limited, and the detection rate of deformable part models decreases.

Method used

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  • Pedestrian Detection Method Based on Weighted Component Model and Selective Search Segmentation
  • Pedestrian Detection Method Based on Weighted Component Model and Selective Search Segmentation
  • Pedestrian Detection Method Based on Weighted Component Model and Selective Search Segmentation

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Embodiment Construction

[0046] The method proposed in this paper will be further explained in combination with the HOG feature pyramid detection process of pedestrians:

[0047] Such as figure 1 In the flow chart of the shown method of the present invention, firstly, the training model is carried out, and the specific process is followed by training samples, initializing the root filter, using standard SVM training, merging containers, using LSVM training, initializing component filters, using LSVM training again, Update component weights to obtain weighted component models. Then image detection is performed, the specific process is to input the image, segment the image (the segmentation process includes selective search, and obtain a useful bounding box), convert the weighted component model into a cascade model, obtain the feature pyramid of the image, and cascade detection , Get the pedestrian area, remove the repeated area, and get the final pedestrian detection result.

[0048] The specific me...

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Abstract

A pedestrian detection method based on weighted part model and selective search segmentation, which consists of a weighted part model training part and a pedestrian detection part. Model construction process: Based on the construction process of the deformable component model, different weights are set for different components according to the different occlusion conditions of pedestrians in crowded scenes, and the hidden support vector machine is used to train the weights. Pedestrian detection process: extract the HOG feature pyramid in the picture, and selectively search and segment the picture to achieve more objects with fewer effective windows. On this basis, cascade detection based on threshold clipping is used. Pedestrian detection. The method of the invention solves the problem of missed detection of pedestrians in a crowded scene from two angles, and has the advantages of reducing interference, improving the accuracy of pedestrian detection, and the like.

Description

technical field [0001] The invention relates to the field of pedestrian detection, in particular to a pedestrian detection method using a weight-based deformable component model and selective search segmentation. Background technique [0002] Pedestrian detection based on static images is to separate the human body appearing in the image from the background and precisely locate it. It is widely used in human-computer interaction, intelligent video surveillance, intelligent transportation and other fields. It is the basis of target classification and behavior understanding. One of the important topics in the field of vision research. However, when pedestrians are the subject of detection, they often appear in very complex backgrounds, and pedestrians have both rigid and flexible characteristics, and their appearance is easily affected by clothing, scale, occlusion, posture and viewing angle, which also makes pedestrian detection It has not only become one of the key points i...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/164G06F18/23
Inventor 闻佳王雪平孔令富
Owner 河北燕大燕软信息系统有限公司
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