Proceedings Third IEEE Workshop on Applications of Computer Vision. WACV'96

DOI: 10.1109/acv.1996.572010

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Identifying nude pictures

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Margaret M. Fleck

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Cited by 56 publications

(27 citation statements)

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“…The pioneer work for identifying adult images by the analysis of image content is proposed by [7], [8], [9], [10]. Their approach combines color and texture properties to obtain a mask for skin regions, which are then fed to a specialized grouper, which attempts to group a human figure using geometric constraints derived from human body structure.…”

Section: Related Workmentioning

confidence: 99%

Nude Detection in Video Using Bag-of-Visual-Features

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et al. 2009

2009 XXII Brazilian Symposium on Computer Graphics and Image Processing

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Abstract-The ability to filter improper content from multimedia sources based on visual content has important applications, since text-based filters are clearly insufficient against erroneous and/or malicious associations between text and actual content. In this paper, we investigate a method for detection of nudity in videos based on a bag-of-visual-features representation for frames and an associated voting scheme.Bag-of-Visual-Features (BoVF) approaches have been successfully applied to object recognition and scene classification, showing robustness to occlusion and also to the several kinds of variations that normally curse object detection methods. To the best of our knowledge, only two proposals in the literature use BoVF for nude detection in still images, and no other attempt has been made at applying BoVF for videos. Nevertheless, the results of our experiments show that this approach is indeed able to provide good recognition rates for nudity even at the frame level and with a relatively low sampling ratio. Also, the proposed voting scheme significantly enhances the recognition rates for video segments, achieving, in the best case, a value of 93.2% of correct classification, using a sampling ratio of 1/15 frames. Finally, a visual analysis of some particular cases indicates possible sources of misclassifications.

“…The pioneer work for identifying adult images by the analysis of image content is proposed by [7], [8], [9], [10]. Their approach combines color and texture properties to obtain a mask for skin regions, which are then fed to a specialized grouper, which attempts to group a human figure using geometric constraints derived from human body structure.…”

Section: Related Workmentioning

confidence: 99%

Nude Detection in Video Using Bag-of-Visual-Features

¹

,

²

,

³

et al. 2009

2009 XXII Brazilian Symposium on Computer Graphics and Image Processing

View full text Add to dashboard Cite

Abstract-The ability to filter improper content from multimedia sources based on visual content has important applications, since text-based filters are clearly insufficient against erroneous and/or malicious associations between text and actual content. In this paper, we investigate a method for detection of nudity in videos based on a bag-of-visual-features representation for frames and an associated voting scheme.Bag-of-Visual-Features (BoVF) approaches have been successfully applied to object recognition and scene classification, showing robustness to occlusion and also to the several kinds of variations that normally curse object detection methods. To the best of our knowledge, only two proposals in the literature use BoVF for nude detection in still images, and no other attempt has been made at applying BoVF for videos. Nevertheless, the results of our experiments show that this approach is indeed able to provide good recognition rates for nudity even at the frame level and with a relatively low sampling ratio. Also, the proposed voting scheme significantly enhances the recognition rates for video segments, achieving, in the best case, a value of 93.2% of correct classification, using a sampling ratio of 1/15 frames. Finally, a visual analysis of some particular cases indicates possible sources of misclassifications.

“…Nowadays the pornographic pictures through the internet fast and strongly affect the physical and mental health of the youth, so the pornographic information detection and filtering technique become a critical research subject in the field of the network cultural security as well as play dramatically important role in the content-based objectionable information detection and filter techniques [1] [2].The paper will be aimed at making the further effort to detect the pornographic information involved in image of Internet by analyzing the factors of human face and skin, and evaluating the acceptability of this kind of objectionable information.…”

Section: Introductionmentioning

confidence: 99%

HSV Color Space and Face Detection Based Objectionable Image Detecting

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et al. 2008

2008 Second International Conference on Future Generation Communication and Networking Symposia

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Internet access has dramatically increased the risk of receiving objectionable information such as the pornographic images. Content based Image detection is of the paramount importance in objectionable images filtering in Internet. This paper designed a simplified system by using the HSV color space converted by the law of gravity center and combining the face detection to define and evaluate the degree of the the benign image in general.

“…How to detect the pornographic videos quickly and accurately and prevent the spread of them effectively has become a hot topic. Most of the current studies remain in the detection of pornographic images [1][2] [3]. Research on the pornographic videos has just started.…”

Section: Introductionmentioning

confidence: 99%

A Pornographic Videos Detection Method Based on Optical Flow Direction's Statistical Histogram

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et al. 2009

2009 International Symposium on Computer Network and Multimedia Technology

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Aimed at that there is often a video paragraph of human body's reciprocating motion in the pornographic videos, a novel method of pornographic videos detection is proposed. On the basis of calculating the optical flow field, we extract the characteristics points of the moving target, and classify optical flow direction of these points and get the statistics of them. Then we establish the optical flow direction's statistical histogram. According to the changes in the direction of moving target and the changes in the frequency of it, we can determine there is pornographic information or not. The experimental results show that the method is simple and convenient, fast and efficient, high in the recognition rate and well in the robustness.

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