Face Detection Gender Recognition 1 1 (19) 1 (1)

Slides:

Advertisements

Similar presentations

Overview of biometric technology. Contents: 1. What is Biometrics The term “biometrics” is derived from the Greek words “bio” (life) and “metrics” (to.

Advertisements

Number Recognition Actually recognizing the symbol representing the number.

Rapid Object Detection using a Boosted Cascade of Simple Features Paul Viola, Michael Jones Conference on Computer Vision and Pattern Recognition 2001.

PERSONAL HYGIENE By: Lyndi, Nick, Ian, and Patrick.

As applied to face recognition.  Detection vs. Recognition.

Neural Network-based Face Recognition, using ARENA Algorithm. Gregory Tambasis Supervisor: Dr T. Windeatt.

Biometrics & Security Tutorial 6. 1 (a) Understand why use face (P7: 3-4) and face recognition system (P7: 5-10)

WP -6: Human Tracking and Modelling Year–I Objectives: Simple upper-body models and articulated tracks from test videos. Year-I Achievements: Tracking.

NTIA Privacy Multistakeholder Meeting March 25, 2014 Amanda Koulousias, Attorney Division of Privacy and Identity Protection Federal Trade Commission FTC.

Sachin Chopra Trevor Garson Madhuri Rapaka Introduction Tool to Tag all your Photographs within minutes 2 – Pass Processing Face Detection – Run the.

Facial Feature Detection

GIP: Computer Graphics & Image Processing 1 1 Medical Image Processing & 3D Modeling.

Instant Recognition of Numbers TEENS base 10 Student instantly recognizes the 10 and the one. Then add the two to make the teen. For example the.

Face Detection And Recognition For Distributed Systems Meng Lin and Ermin Hodžić 1.

 Face Detection Face Detection  Eye Detection Eye Detection  Lip-reading Lip-reading  Facial Feature Detection Facial Feature Detection  Gaze Tracking.

Obtaining Data for Face Recognition from the web By Tal blum Advisor: Henry Schneiderman.

Overview of Part I, CMSC5707 Advanced Topics in Artificial Intelligence KH Wong (6 weeks) Audio signal processing – Signals in time & frequency domains.

Smart Offloading for Mobile Cloud Applications Francisco Airton PhD Student Orientador: Paulo Maciel.

Model of the Human  Name Stan  Emotion Happy  Command Watch me  Face Location (x,y,z) = (122, 34, 205)  Hand Locations (x,y,z) = (85, -10, 175) (x,y,z)

 Motivated by desire for natural human-robot interaction  Encapsulates what the robot knows about the human  Identity  Location  Intentions Human.

Machines that Make Decisions Instructor: Edmondo Trentin

CS332 Visual Processing Department of Computer Science Wellesley College CS 332 Visual Processing in Computer and Biological Vision Systems Overview of.

Final Year Project Vision based biometric authentication system By Padraic ó hIarnain.

7 Fun Things to do with MapReduce Chris Hillman – Teradata Data

Ch 3: Social Beliefs & Judgments Part 1: Sept. 7, 2012.

Face Detection and Gender Recognition EE368 Project Report Michael Bax Chunlei Liu Ping Li 28 May 2003.

BACKGROUND MODEL CONSTRUCTION AND MAINTENANCE IN A VIDEO SURVEILLANCE SYSTEM Computer Vision Laboratory 指導教授：張元翔老師研究生：許木坪.

Case study: Plan UK Plan UK’s objective was to highlight the lack of choices girls in developing nations have, as opposed to those in the UK. As a result,

Working With WarKing. Overview Strengths and Weaknesses of the Scribbler Easiest, Hardest, Coolest Secret Weapons.

IBM - CVUT Student Research Projects IBM Presence detection Milan Stezka

Parts of the Clock Click on the minute hand. Click on the clock’s face.

IBM - CVUT Student Research Projects IBM Presence detection Milan Stezka

Content-Aware Image Resizing Jack Breese Computer Systems Quarter 1, Pd. 7.

HCI 575X Project Madhuri Rapaka Sachin Chopra Trevor Garson.

Copyright 2007 by Rombix. R CyClops is a computer vision solution which could integrate most of the Real World Computer Vision Application. Available.

3D Laser Scanner & Survey Equipment in Sharjah

Course Outline (6 Weeks) for Professor K.H Wong

Day 3: computer vision.

Nicole looks at faces Development of a visual robot interface to interpret facial expressions NICOLE: Future robots will share their environment with humans.

Kickoff meeting January, 2011

Face Detection for Access Control

New Feature Introduction - Internal

O ‘ clock times- PowerPoint months

Viseum iVOS FaceRec HOW IT WORKS

Deep sensing with wearable devices

Gender stereotypes and me

ECE533 – Image Processing Project Face Recognition Techniques

Face Recognition App - Sara Analytics

Quicken support number Quicken support number

بلکه ” ما“ شود تقدیم به او که نمی خواهد من و تو ” ما“ شویم

Group 1: Gary Chern Paul Gurney Jared Starman

Video Processing Steps Face Detection Activity Recognition

جامعة الكويت كلية الآداب- قسم الإعلام مدخل الى علم الإعلام

Situation of LGBT people in Kazakhstan ILGA-Europe, Athens 2015

Face Components detection

First Homework One week

Wearable Visual Information Systems (VINST)

Cheng-Yi, Chuang (莊成毅), b99

T H E P U B G P R O J E C T.

Gender stereotypes and me

Gender stereotypes and me

Half past- PowerPoint months

Natural User Interaction with Perceptual Computing

Anarghya Mitra and Zelun Luo

Example segmentations - unseen images

Applications Discussion

Sources of Information

Genetic Variation Most genes have small sequence differences between individuals Occur every 1350 bp on average Some of these polymorphisms may affect:

The #BalanceforBetter action I will take to progress gender parity is

Week 1 Emily Hand UNR.

Presentation transcript:

Face Detection Gender Recognition 1 1 (19) 1 (1) 2 3 4 5 6 7 8 9 10 11 1 (19) 1 (1) 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Face Detection Gender Recognition 1 3 (19) 2 (1) 2 2 (20) 4 (0) 3 3 (19) 2 (1) 2 2 (20) 4 (0) 3 4 (18) 4 5 9 (13) 6 5 (17) 7 7 (16) 8 8 (14) 1 (2) 9 1 (22) 10 11 12 13 14 15 16 17

Face Detection Gender Recognition 1 4 (19) 2 (1) 2 2 (20) 5 (0) 3 5 (18) 4 5 10 (13) 6 7 (17) 7 8 (16) 8 9 (14) 1 (2) 9 1 (22) 10 11 12 13 14 15 16 17

Face Detection Gender Recognition 1 4 (19) 2 (1) 2 2 (20) 5 (0) 3 5 (18) 4 5 10 (13) 6 7 (17) 7 8 (16) 8 9 (14) 1 (2) 9 1 (22) 10 11 11 (08) 12 13 14 15 16 17

Face Detection Gender Recognition 1 4 (19) 2 (1) 2 2 (20) 5 (0) 3 6 (18) 4 5 11 (13) 6 8 (17) 7 9 (16) 8 10 (14) 1 (2) 9 1 (22) 10 11 12 (08) 12 13 14 15 16 17

Face Detection Gender Recognition 1 4 (19) 2 (1) 2 2 (20) 5 (0) 3 7 (18) 4 5 12 (13) 6 9 (17) 7 10 (16) 8 11 (14) 1 (2) 9 1 (22) 10 11 13 (08) 12 13 14 15 16 17

Face Detection Gender Recognition 1 4 (19) 2 (1) 2 2 (20) 5 (0) 3 8 (18) 4 5 13 (13) 6 10 (17) 7 11 (16) 8 12 (14) 1 (2) 9 1 (22) 10 11 14 (08) 12 13 14 15 16 17

Face Detection Gender Recognition 1 4 (19) 2 (1) 2 2 (20) 5 (0) 3 9 (18) 4 5 14 (13) 6 11 (17) 7 12 (16) 8 13 (14) 1 (2) 9 1 (22) 10 11 15 (08) 12 13 14 15 16 17

Face Detection Gender Recognition 1 5 (19) 2 (1) 2 3 (20) 5 (0) 3 10 (18) 4 5 15 (13) 6 12 (17) 7 13 (16) 8 14 (14) 1 (2) 9 1 (22) 10 11 16 (08) 12 13 14 15 16 2 (21) 17

Face Detection Gender Recognition 1 6 (19) 2 (1) 2 3 (20) (18.83) 5 (0) 3 11 (18) 4 5 16 (13) 6 13 (17) 7 14 (16) 8 15 (14) 1 (2) 9 1 (22) 10 3 (20) (11.68) 11 17 (08) 12 13 14 15 16 2 (21) 17 3 (20) (18.16)

Face Detection Gender Recognition 1 6 (19) 2 (1) 2 3 (20) (18.83) 5 (0) 3 11 (18) 4 5 16 (13) 6 13 (17) 7 14 (16) 8 15 (14) 1 (2) 9 1 (22) 10 3 (20) (11.68) 11 17 (08) 12 13 14 15 16 2 (21) 17 3 (20) (18.16)