'Integral image' diaporamas de présentation

Ch. 6: Face detection

Ch. 6: Face detection. KH Wong. Introduction. Face interface Face detection Face recognition. Face database. Output:. Mr.Chan Prof..Cheng. Face detection. Face recognition. Face detection [1]. To detect faces in an image (Not recognize it yet) Challenges

1.29k views • 62 slides

ENGG6530 Reconfigurable Computing Systems Instructor: Dr. Shawki Areibi

ENGG6530 Reconfigurable Computing Systems Instructor: Dr. Shawki Areibi. “Flexible Parallel Hardware Architecture for AdaBoost -Based Real-Time Object Detection” Presenter: Ziad Abuowaimer Date: March 17, 2014. Outline. AdaBoost real-time object detection algorithm: Haar -like features.

630 views • 46 slides

Comput ing Sum of Pixels in a Rectangle and Haar-Like Features by Strip Sum

Comput ing Sum of Pixels in a Rectangle and Haar-Like Features by Strip Sum. Student: Wanli Ouyang ?????? Supervisor: Prof. W.K. Cham The Chinese University of Hong Kong. Outline. Introduction The proposed algorithm Experimental result Conclusion. Outline. Introduction

593 views • 40 slides

Comput ing Sum of Pixels in a Rectangle and Haar-Like Features by Strip Sum

Comput ing Sum of Pixels in a Rectangle and Haar-Like Features by Strip Sum. Student: Wanli Ouyang ?????? Supervisor: Prof. W.K. Cham The Chinese University of Hong Kong. Outline. Introduction The proposed algorithm Experimental result Conclusion. Outline. Introduction

403 views • 40 slides

REAL TIME FACE DETECTION

REAL TIME FACE DETECTION . Justin Rilling Pooja Mhapsekar Moinuddin Sayed Ogom J Obinor. Introduction. The idea is to be able to detect faces appearing in an image. The faces can be of different sizes and orientations.

558 views • 35 slides

Lecture 09

Lecture 09. 03/01/2012 Shai Avidan. ?????: ????? ?????? ??? ????? ????? ????? ??? ?? ?????? / ?? ????? ?????. Today. Viola Jones Face Detection : Integral Images. Gentle AdaBoost . Attentional Cascade. Many slides adapted from P. Viola. Integral Images.

478 views • 31 slides

SURF: Speeded Up Robust Features

SURF: Speeded Up Robust Features. ???? : ??? ?? Group number: 20 Advisor: Tzuu-Hseng S. Li Group members: E24956552 ??? E24951099 ??? N26984224 ??? aiRobots Laboratory, Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan, R.O.C. Outline.

899 views • 30 slides

Paul Viola Mike Jones MERL Compaq Cambridge MA

Learning to Detect Faces Rapidly and Robustly. Hierarchy of Visual Attention Operators Automatic Selection of Discriminative Features. Paul Viola Mike Jones MERL Compaq Cambridge MA. Face Detection Example. Many Uses - User Interfaces - Interactive Agents

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Viola/Jones: features

585 views • 27 slides

Fast and Robust Classification using Asymmetric AdaBoost and a Detector Cascade

Fast and Robust Classification using Asymmetric AdaBoost and a Detector Cascade. Paul viola and Michael Jones. Outline. Motivation and objective Definition of feature vectors Asymmetric Adaboosting Experiments and Results Conclusions. Motivation.

387 views • 24 slides

SURF : Speeded-Up Robust Features

CPSC 643, Presentation 2. SURF : Speeded-Up Robust Features. Herbert Bay a , Andreas Ess a , Tinne Tuytellares b , Luc Van Gool a,b a ETH Zurich b K. U. Leuven, ESAT-PSI Sternwartstrasse 7 Kasteel Arenberg 10

2.75k views • 19 slides

Rapid Object Detection using a Boosted Cascade of Simple Features

Rapid Object Detection using a Boosted Cascade of Simple Features. Author ? Paul Viola, Michael Jones Conference on Computer Vision and Pattern Recognition 2001 Speaker ? Liu, Yi- Hsien. Outline. Introduction Features Integral Image AdaBoost Cascade Conclusions. Introduction.

313 views • 12 slides