Panasonic IDguard User Manual

Identity Redaction

Solution

As digital content increases as a result of body-worn cameras & in-car videos, the ability to automate time consuming manual processes for video redaction enables agencies to streamline file editing tasks and respond quickly to Freedom of Information Act (FOIA) requests.

CLOUD BASED OR ON-PREMISE SOLUTION, WORKING INDEPENDENT OF OTHER EVIDENCE MANAGEMENT SYSTEMS Panasonic combines its AI and machine learning technology to automate the video redaction process.

•IDguard reduces manual processes of uploading, storing, searching, editing and sharing content, to save time and money

•Redacting through IDguard speeds-up the time required to release videos to the public

•Comprehensive administrative tools provide strict, secure, multi-user management with critical editing capabilities

•Microsoft’s Azure service creates an unmatched platform with its integrated cloud approach, enabling its users to invest in state-of- the-art technology.

EASY-TO-USE INTERFACE

IDguard boasts a simple UI, empowering users to focus on content

•Easily adjust proper identification settings to blur images from the master video file

•All videos are copies of the original video for evidence management

•Improve investigators’ reach by providing fast, accessible information

•Increase accuracy through reduction of human interaction with files

KEY FEATURES & BENEFITS

SPEEDS FOIA REQUESTS	ARTIFICIAL	INGESTION API’s	HIGHLY EFFICIENT	AZURE CLOUD OR
Fulfill FOIA requests in	INTELLIGENCE	For UDE & UEMS,	Reduces manual effort	ON PREMISE
record time through	Increases accuracy	making integration	associated with	Configure with
process automation	by reducing human	with existing	editing sensitive files	cloud based or
	intervention	systems easy	by up to 90%	on premise solution

LEARN MORE AT na.panasonic.com/IDguard

*Productivity gain results are based on internal Panasonic testing and pertain only to video use case. Your results may vary based on user variables. IDguard application video processing time and resulting redaction capability is dependent on the number of faces within the video, clarity of facial image, system hardware configuration and user interaction.