Automatic content filtering
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Automatic Content Filtering. KDDI R&D Laboratories Inc. UGC(User Generated Content) is very popular and becoming a high part of online volume. Industry sources tell us that YouTube content submissions are moving to 5M minutes of new content uploads per day

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Automatic Content Filtering

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Automatic content filtering

Automatic Content Filtering

KDDI R&D Laboratories Inc.


Automatic content filtering

UGC(User Generated Content) is very popular and becoming a high part of online volume.

Industry sources tell us that YouTube content submissions are moving to 5M minutes of new content uploads per day

A large variety of formats, resolutions and sizes of videos and images are uploaded to the internet daily

How can a company can check all this picture and movie content?

Drawbacks of Manual checking :

Subjective evaluation is time and resource consuming

Subjective evaluation introduces fluctuations in results

What are the key drivers for automatic content filtering?

High speed

High accuracy

Background


Content filtering block diagram

Content Filtering Block Diagram

Performance

Can operate 55Pics/sec. using only Laptop PC

Off Line

Online

OK Image

Database

NGImage

Database

Input Images

Feature Extraction

Feature Extraction

Dictionary

Detection

Training (iSVM)

Strong Point-1

Adopt proprietary image features

OK Image

NG Image

Strong Point-2

Fast training by introducing iSVM

3


High speed training by incremental svm isvm

High Speed Training by Incremental SVM (iSVM™)

SVM (Support Vector Machine) : Concept and Problem

Concept : Mapping to multidimensional space and determining boundary between OK/NG

Problem :Huge calculations are needed to support working on these huge datasets.

Conventional SVM cannot handle a huge training dataset

There’s a Strong Need for Fast Training Algorithm while maintaining high accuracy

Incremental SVM (iSVM) : Concept, Features, Benefit

Introducing KDDI R&D Labs’ proprietary adaptive training algorithm - iSVM

Now calculation cost increases are proportional to the amount of data!

Conventional methods SVM cube the proportion of calculation to data!!!

We have confirmed that iSVM accelerates calculation speeds

up to 8X for 5,000,000 training datasets.


Performance comparison

Performance Comparison

1.0

High

良い

Other

KDDI R&D

0.8

KDDI R&D

0.6

Other

Accuracy

0.97

0.975

0.4

0.697

0.643

0.2

Low

悪い

0.0

Recall

Precision

100

Slow

80

60

5X faster than other product

msec/content

Speed

90

40

20

18

Fast

0

Other

KDDI R&D


Automatic content filtering

Demo

  • Training Datasets

    • Top half : Training images for OK.

    • Bottom half : Training images for NG.

  • Input images obtained from the internet

    • 200 images are arbitrary obtained.

  • Detection result using other product

    • Some NG pictures are detected as OK.

    • About 10% in this case.

  • Detection result using KDDI R&D Labs.

    • Almost all NG pictures are detected as NG.

    • Accuracy is far better than other product.


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