Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Face recognition based multi-camera video event retrospective trace method

A face recognition and video event technology, applied in computer parts, character and pattern recognition, instruments, etc., can solve the problems of low retrieval efficiency, time-consuming and labor-intensive video events, etc.

Inactive Publication Date: 2015-07-01
南京华控创为信息技术有限公司
View PDF2 Cites 24 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a multi-camera video event retrospective tracking method based on face recognition to solve the problems of time-consuming, labor-intensive and low retrieval efficiency in manually viewing video events

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Face recognition based multi-camera video event retrospective trace method
  • Face recognition based multi-camera video event retrospective trace method
  • Face recognition based multi-camera video event retrospective trace method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0075] The present invention will be described in detail below with reference to the drawings and specific embodiments.

[0076] see figure 1 , a kind of face recognition-based multi-camera video event retrospective tracking method of the present invention is specifically implemented according to the following steps:

[0077] Step 1: Train the face cascade classifier through the Adaboost method based on Haar-like features. The specific process is as follows:

[0078] In face detection, each weak classifier that composes the strong classifier trained by the Adaboost algorithm corresponds to a Haar-like feature, which is the optimal weak classifier based on this feature, representing the grayscale of a certain part of the face distribution characteristics. Since not every face feature described by Haar-like features is important, it can be used as a feature to distinguish between a face and a non-face, so the Adaboost algorithm needs to be iteratively selected from these very ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a face recognition based multi-camera video event retrospective trace method. The face recognition based multi-camera video event retrospective trace method comprises the steps of firstly training a face cascade classifier by adopting an Adaboost method based on a Haar-like feature, then adopting the face cascade classifier to detect and tracing faces existing in each camera so as to obtain a face library, framing face zones of pedestrians in videos, extracting the LBP features of the face zones, conducting matching recognition on target faces in the face library, finally extracting the time of targets existing in all cameras to obtain walking routes according to face recognition results so as to obtain retrospective trace results of the targets. The face recognition based multi-camera video event retrospective trace method is applied in multiple camera video system in multiple scenes and used for retrospection of video events, the working amount of manual video inquiry is reduced, and inquiry efficiency is improved.

Description

technical field [0001] The invention belongs to the technical field of intelligent analysis systems, and in particular relates to a multi-camera video event retrospective tracking method based on face recognition. Background technique [0002] Video surveillance systems are everywhere in people's lives. When an abnormal event occurs, it is usually necessary to find suspicious personnel targets from the surveillance video. The traditional method is often to check manually. Due to the large amount of video surveillance data, manual search is time-consuming, labor-intensive and inefficient, and it is easy to miss a lot of useful information. Therefore, through the processing of monitoring data by machines, the intelligent realization of backtracking has important practical application value. [0003] For the pedestrian target in the video, although there are many kinds of features, the human face is a reliable and superior biometric feature. In recent years, with the continuo...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06K9/00G06K9/66G06K9/46
Inventor 张二虎白晓楠张卓敏
Owner 南京华控创为信息技术有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com