Computer Vision No. 1 What is the Computer Vision?

Instructor u Katsushi Ikeuchi u Pointers: Komaba Meguro-ku

Evaluation u attendance 50% u report 50%

Schedule u Shape-from-X –Analysis of line-drawing –Shape-from-shading –Binocular stereo u Interpretation –Interpolation –Representation u Special topics –Modeling from reality

Katsu Ikeuchi U. Tokyo Human visual system MIT AI Shape-from-shading ETL Object recognition CMU Assembly plan from observation Modeling from reality U. Tokyo Virtual heritage

Demonstration Videos

Photometric Stereo (1980) u Brightness difference -> 3D shape u 3D shape -> 3D Pose determination u 3DPose -> Grasping

Bin Picking

Assembly Plan from Observation (1990)

Recent Result Assembly plan from observation

Learning Human Dance

Motion Capture Data

Robot Dancing

Modeling Cultural Heritage

Virtual City Probe Info

Virtual City Speed ： 10km/h Vehicle Pedestrian Near Yoyogi park

Computer Vision (CV) u To make a computer to recognize the 3D world as we do u To generate 3D representations from 2D images

CV and related areas Image Understanding (AI) Pattern Recognition (Mathematical theories) Image Processing (Signal processing)

CV and related areas Image Understanding (AI) Pattern Recognition (Mathematical theories) Image Processing (Signal processing)

Image Processing To get better images: 2D-to-2D

CV and related areas Image Understanding (AI) Pattern Recognition (Mathematical theories) Image Processing (Signal processing)

Pattern Recognition Decision making: mathematical theories

CV and related areas Image Understanding (AI) Pattern Recognition (Mathematical theories) Image Processing (Signal processing)

Image Understanding Scene description

Why difficult ? u A lot of data u Ambiguity –Projection of a 3D world to a 2D image u Many factors to influence the image –Illumination condition –Object shape –Camera characteristics

Image Foggy golden triangle in Pittsburgh

But …

A lot of data u Landsat image –1scene: 3300 x 2300 x 4 = bytes –200 scenes/ day u Color TV image –512 x 512 x 3 x 30 = bytes/sec

Why difficult ? u A lot of data u Ambiguity –Projection of a 3D world to a 2D image u Many factors to influence the image –Illumination condition –Object shape –Camera characteristics

Illusion due to the projection

Why difficult ? u A lot of data u Ambiguity –Projection of a 3D world to a 2D image u Many factors to influence to the image –Illumination condition –Object shape –Camera characteristics

Image u A image is a matrix of pixels u Each pixel –brightness –Color –Distance

Inside and Outside (Gestalt)

Common sense u To formulate the common sense → research topics

Current issues u A lot of data –Computational sensor –Vision board u Ambiguity –Projective geometry –constraints u Many factors –Physics-based vision

Application areas

What is Computer Vision? u Vision is … an information processing task that constructs efficient symbolic descriptions of the world from images. (Marr) u Vision is … inverse graphics. u Vision is … looks easy, but is difficult. Vision is … difficult, but is fun. (Kanade) u Vision is an engineering science to create an alternative of human visual systems on computers （ Ikeuchi ）

References u Journals –Inter. J. Computer Vision –IEEE Trans. Pattern Analysis and Machine Intelligence –IEICE D-2 –IPSJ Trans CVIM u International conferences –Inter. Conf. Computer Vision (ICCV) –Computer Vision and Pattern Recognition (CVPR) –Asian Conf. Computer Vision (ACCV) u Special interest groups –IPSJ CVIM –IEICE PRMU

Schedule (April-May) 4/12 Introduction 4/19 Line drawing 4/26 Perspective projection 5/3 Holiday 5/10 Shape from Shading 5/17 Color Dr. Miyazaki 5/24 Stereo#1 5/31 Stereo#2 Dr. Vanno and Dr. Ogawara

Schedule (June-July) 6/7 Motion analysis 6/14 No class 6/21 EPI, IBR & MBR Dr. Ono 6/28 Interpolation 7/5 Object representation#1 Dr.Takamatsu 7/12 Object representation#2