A Tour in the Real-World Challenges Faced by Law Enforcement Agencies When Dealing With Images

Explore the complex challenges faced by law enforcement agencies when dealing with image and video evidence in this 59-minute webinar presented by Dr. Martino Jerian. Delve into the intricacies of forensic video analysis, examining issues such as infrared footage interpretation, lens distortion, perspective tricks, color fidelity, and compression artifacts. Learn about proprietary video formats, image enhancement techniques, and the importance of proper evidence processing. Discuss the impact of artificial intelligence, deepfakes, and cybersecurity on forensic analysis. Gain insights into correctly working with image and video evidence, understanding guidelines, and recognizing the limitations and potential of forensic video analysis in law enforcement applications.

Intro
ABOUT ME
WHAT WE DO
WHY THIS PRESENTATION?
WHAT IS FORENSIC VIDEO ANALYSIS?
WHY IS IT SO HELPFUL?
WHAT ARE THE ISSUES
VIDEO EVIDENCE SEEMS EASY, BUT IT'S ACTUALLY EASY TO GET IT WRONG
INFRARED: DON'T TRUST THE COLORS OF MOST CCTV FOOTAGE AT NIGHT
ANOTHER EXAMPLE
LENS DISTORTION: CAMERAS MAY CHANGE THE SHAPE OF THINGS
PERSPECTIVE: SIZE COMPARISON MAY BE TRICKY
COLOR FIDELITY IT'S HARD TO OBJECTIVELY EVALUATE COLORS ON VIDEO
WHAT COLORS DO YOU SEE?
COMPRESSION ARTIFACTS: HIDING OR ADDING DETAILS TO THE SCENE
VIDEO COMPRESSION
WHAT IS THIS...
PROPRIETARY VIDEO FORMATS
PROPRIETARY PLAYERS
SOMETHING WENT WRONG!
HOW NOT TO EXPORT
IMAGE QUALITY AND ENHANCEMENT/RESTORATION
PERSPECTIVE CORRECTION, DEBLURRING
DEINTERLACING, HISTOGRAM EQ, STABILIZATION, FRAME INTEGRATION, SHARPENING
EXPOSURE, STABILIZATION AND FRAME INTEGRATION
PERSPECTIVE STABILIZATION AND SUPERRESOLUTION
DEBLURRING A SCREEN PHOTO
I NEED THAT LICENSE PLATE... BORDERLINE!
WHAT CAN WE DO?
PROCESSING REQUIREMENTS FOR EVIDENTIARY USE
WHICH KIND OF ALGORITHMS ARE ACCEPTABLE?
THE IMAGE GENERATION MODEL
TRUST. DEEPFAKES, MANIPULATION, AND MISATTRIBUTION
FORENSIC VIDEO ANALYSIS: INTERPRETING IN THE RIGHT WAY WITHOUT BIAS
WE SEE WHAT WE WANT TO SEE
MEASURING HEIGHT
SPEED ESTIMATION
JUDGES AND JURIES ARE EASY TO MISLEAD ON TECHNICAL TOPICS
IMPACT OF ARTIFICIAL INTELLIGENCE
Al/ML/DEEP LEARNING ISSUES
GOING TO THE AVERAGE
BALANCE BETWEEN PRIVACY AND SECURITY
CYBERSECURITY
AMPED SOFTWARE
HOW TO CORRECTLY WORK ON IMAGE AND VIDEO EVIDENCE?
GUIDELINES
WHAT CAN WE OBTAIN?
CONCLUSIONS