GPU accelerated face detection from low resolution surveillance videos using motion and skin color segmentation

Mutneja, Vikram; Singh, Satvir

doi:10.1016/j.ijleo.2017.11.188

Cited by 9 publications

(3 citation statements)

References 17 publications

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“…As the masking module performs masking on objects that have been recognized by the object identification module, the access permission DB module holds authentication information that discerns the status of the access permission granted to the user on each object (allowed vs. denied) and offers authentication information regarding each object upon requests from the masking module. Depending on the level of access rights stored in the access permission DB module, requesters of visual information may obtain different results from the same visual information due to the difference in the scope of masking provided [62][63][64][65].…”

Section: Access Permission Db Modulementioning

confidence: 99%

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A Mechanism of Masking Identification Information regarding Moving Objects Recorded on Visual Surveillance Systems by Differentially Implementing Access Permission

Park

Kim

2019

Electronics

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Video surveillance systems (VSS), used as a measure of security strengthening as well as investigation, are provided principally in heavily crowded public places. They record images of moving objects and transmit them to the control center. Typically, the recorded images are stored after being encrypted, or masked using visual obfuscations on a concerned image(s) in the identification-enabling data contained in the visual information. The stored footage is recovered to its original state by authorized users. However, the recovery entails the restoration of all information in the visual data, possibly infiltrating the privacy of the object(s) other than the one(s) whose images are requested. In particular, Artificial Intelligence Healthcare that checks the health status of an object through images has the same problem and must protect the patient's identification information. This study proposes a masking mechanism wherein the infiltration of visual data privacy on videos is minimized by limiting the objects whose images are recovered with differential use of access permission granted to the requesting users.

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Section: Access Permission Db Modulementioning

confidence: 99%

“…visual information may obtain different results from the same visual information due to the difference in the scope of masking provided [62][63][64][65].…”

Section: Comparisons Amongst Privacy Masking Techniques and Devicesmentioning

confidence: 99%

A Mechanism of Masking Identification Information regarding Moving Objects Recorded on Visual Surveillance Systems by Differentially Implementing Access Permission

Park

Kim

2019

Electronics

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“…Accordingly, the public's interest in intelligent visual surveillance systems (IVSSs) is growing, as the system combines technologies that allow the understanding of the scenes of incidents/accidents and the behavioral patterns of the objects, to predict incidents/accidents and warn the VSS users, and prevent the leakage of personal information [4][5][6][7]. An IVSS thus records the persons in areas targeted for recording to help understand the locations and detect the faces of the persons so that they can be used as the basis for assessment and decision-making [8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

A Face Image Virtualization Mechanism for Privacy Intrusion Prevention in Healthcare Video Surveillance Systems

Kim

Park

2020

Symmetry

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Closed-circuit television (CCTV) and video surveillance systems (VSSs) are becoming increasingly more common each year to help prevent incidents/accidents and ensure the security of public places and facilities. The increased presence of VSS is also increasing the number of per capita exposures to CCTV cameras. To help protect the privacy of the exposed objects, attention is being drawn to technologies that utilize intelligent video surveillance systems (IVSSs). IVSSs execute a wide range of surveillance duties—from simple identification of objects in the recorded video data, to understanding and identifying the behavioral patterns of objects and the situations at the incident/accident scenes, as well as the processing of video information to protect the privacy of the recorded objects against leakage. Besides, the recorded privacy information is encrypted and recorded using blockchain technology to prevent forgery of the image. The technology herein proposed (the “proposed mechanism”) is implemented to a VSS, where the mechanism converts the original visual information recorded on a VSS into a similarly constructed image information, so that the original information can be protected against leakage. The face area extracted from the image information is recorded in a separate database, allowing the creation of a restored image that is in perfect symmetry with the original image for images with virtualized face areas. Specifically, the main section of this study proposes an image modification mechanism that inserts a virtual face image that closely matches a predetermined similarity and uses a blockchain as the storage area.

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Fast Implementation of Face Detection Using LPB Classifier on GPGPUs

Ikbal¹,

Fayez²,

Fouad³

et al. 2019

Advances in Intelligent Systems and Computing

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GPU accelerated face detection from low resolution surveillance videos using motion and skin color segmentation

Cited by 9 publications

References 17 publications

A Mechanism of Masking Identification Information regarding Moving Objects Recorded on Visual Surveillance Systems by Differentially Implementing Access Permission

A Mechanism of Masking Identification Information regarding Moving Objects Recorded on Visual Surveillance Systems by Differentially Implementing Access Permission

A Face Image Virtualization Mechanism for Privacy Intrusion Prevention in Healthcare Video Surveillance Systems

Fast Implementation of Face Detection Using LPB Classifier on GPGPUs

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