The document introduces Yuichi Yaguchi Laboratory's image processing research. It discusses using the Time-Space Continuous Dynamic Programming (TSCDP) method to detect gestures from camera input and create a gesture interface. The researcher aims to evaluate TSCDP's performance through experiments detecting gestures like right, left, up and down with and without occlusion. Future work includes improving TSCDP tracking, combining it with other methods, comparing other gesture detection techniques, and enhancing the TSCDP gesture interface.

1. Image Processing Laboratory
Yuichi Yaguchi Laboratory
s1170133 Keigo Amma

2. Introduction
 In the scene of computing, we can see
various gesture interface for standard
family use. such as mouse, remote
controller for TV, kinect, etc.
 There are many techniques to detect
human gesture or posture for
recognizing each gesture.

3. Background, related work
 Gesture detect with image processing
 Model base
○ DP,particle filter, kalman filter
 Feature base
○ SIFT, Harris corner,Hog
 Machine learning
○ Boosting(Ada boost),SVM
There are three genarally field.
Many of existing method have week point that not
strong occlusion, difficult malti-detection, need to
combine another method etc…

4. Motivation
 I want to make useful interface and confirm
performance metohd of the interface.
 I use method Time-Space Cointinuous
Dynamic Programming(TSCDP) to make
interface (T.Matsuzaki (2012) MIRU)
 My thesis problem is to evaluate the
method performance by experiment with
implemented gesture interface

5. What’s TSCDP
 TSCDP, which short for Time-Space
Continuous Dynamic Programming
 The algorithm detect specific motion which
given by movie.
 Strong occlusion, multi-tracking
movie
…
Point and Time
INPUT TSCDP OUTPUT of existing
trajectory
trajectory(point,color
)

6. Experiment, Environment
 Envioronment
 One USB Web camera
 1 Frame size 40x30 (now adjusting…)
 Usual complex back ground(My lab back
ground)
 Experiment
 Gesture(right, left, up, down, circle) detection
rate.
 Each experiment test 5 people
 Try 100 each gesture
 Case have a occlusion.

7. Result(not yet)
 Gesture rate
 Right ???/100
 Left ???/100
 Up ???/100
 Down ???/100
 Circle ???/100
 Gesture rate(Occlusion)
 Right ???/100
 Left ???/100
 Up ???/100
 Down ???/100
 Circle ???/100

8. Future work
 TSCDP Not only gesture tracking
 Combination TSCDP and another
method For tracking
 Compare other gesture detection
 Improve TSCDP gesture Interface