T2018: SkyNet owns us

Raúl Roa

Who's this guy

Lead Software Architect

WE MAKE COMPUTERS DO AMAZING THINGS...

PUT STUFF WHERE THEY BELONG

I DO MORE

Chief Technology Officer at Yoyo

Payment facilitator for small businesses

Technical Adviser & Business partner at Digital Reality
Virtual Reality and augmented reality for developing countries.

 

Business & Technical Consultant at ITSS GLOBAL
Banking technology solutions and services to banks and financial institutions

 

Minor OSS contributor

DevIL, ResIL, fog, Emscripten

 

A LITTLE BIT MORE...

Full Stack Developer (10+ years)
C/C++, Python, Rust, MCP, MCAD and MCSD

2D/3D Game Developer (5+ years)
C/C++, UnrealScript, Lua, GLSL, HLSL, Unreal Engine, Unity

Adjunct Lecturer PUCMM (RSTA, STI) (7 years)
Software Engineering, Programming, Data Structures
 

DCGames (2003 ― 2005)
Game performance metrics for CS 1.6, Unreal Tournament, Quake 3 and Warcraft: Frozen Throne. Biggest video game related site in the Caribbean. Subsequently acquired by Verizon in 2005.

 

what's this talk about?

TERMINATOR... OF COURSE

SERIOUSLY...

IF WE TRIED TO, WE COULD ACTUALLY BUILD TERMINATORS TODAY

LET'S BREAK IT DOWN

T-1000 FEATURES

• DOESN'T TALK
• MORPHS INTO A SMALL DOG
• IDENTIFIES THE PERSON OF INTEREST
  • AGE
  • GENDER
  • SENTIMENT
• FOLLOWS THE PERSON OF INTEREST
• IT KNOWS WHAT OBJECTS ARE AND HOW TO USE THEM

WAIT... HOW IS THIS EVEN POSSIBLE?

BECAUSE OF BUZZ WORDS!

BUT WHY ARE THESE THINGS IN OUR HANDS NOW?

3 DRIVING FORCES...

• COMPUTING POWER
   
• DATA AVAILABILITY
   
• BETTER ALGORITHMS

LET'S START...

John Connor is a person of interest

WE KNOW HOW HE LOOKS LIKE...

HOW CAN WE TRACK HIM?

FACE RECOGNITION PIPELINE

SOME OF THE ALGORITHMS

MOST USED FACE RECOGNITION ALGORITHMS

• VIOLA-JONES (HAAR)
   
• HISTOGRAM ORIENTED GRADIENT (HOG)
   
• CONVOLUTIONAL NEURAL NETWORKS (CNN)

HAAR CASCADING IN ACTION

AVAILABLE TOOLS

COMMERCIAL OPTIONS

OPEN SOURCE OPTIONS

• AMAZON REKOGNITION
   
• MICROSOFT COGNITIVE SERVICES

 

• OPENFACE
   
• dlib

 

THE CHALLENGE

CHALLENGES

• DATA COLLECTION
   
• DATA CURATION
   
• DATA QUALITY
   
• NO ONE SIZE FITS ALL
   
• SPEED vs ACCURACY

PIPELINE

1. FACE DETECTION
    
2. FACIAL LANDMARKS DETECTION
    
3. FACE ENCODINGS
    
4. FACIAL RECOGNITION

 

GOING FURTHER!

THINGS TO ADD

• METADATA TO IMAGES/VIDEOS
   
• EXTRACT SENTIMENT
   
• OBTAIN PERSONALITY TRAITS

HASTA LA VISTA BABY!