Yo 
ps 
tal 
nd 
sal 
ed 
ne 
ial 
ed 
ord 
  
115 
  
= i i Ux Toe 
Xeesb|cosfaen sin (ki+k o)-cos(a+wo)sin (k J) dam) 
4 > Head 
Yerleseesoen oor ono) (2) 2 FA A LA 
| Je NÉ AN 
2,=2;-D[sin (e+w}-sin(a+ne)) 5 10 20 40 50 60 70 B6 90 N (m) 
2 Sn 
where; | 
Xo, Yo,2o ; camera position of the orientation image 4 
Xo: Yo,Zo ; camera position of a sequential image (a) Horizontal errors 
D ; distance from the theodolite center to the lens center of the 
CCD camera —X— Toe 
(mm) 
a. ; clockwise angle from the line perpendicular to the optical 
4 
sight line of the theodolite to the lens center of the CCD camera | AX 
(2, ; € Of the orientation image ( = — Vo) 2 X a > x 
0 L 1 1 i 
0 ; o of a sequential image ( - — V) 10 20 30 20 50 60 "EST 90/100 (m) 
Ko ; x of the orientation image ( = Ho) 2 
K, ; x of a sequential image (=(H; — Hp) + 9) 
H; <0 in the counterclockwize case 4 
Ho, Vo ; horizontal and zenith angles of the orientation image 
Hi, V ; horizontal and zenith angles of a sequential image 
——o——- Head 
(b) Vertical errors 
Figure 8 Errors in the feature points 
Figure 8 shows the horizontal and vertical errors of the feature points measured in the simulated 100 meter race. 
2-3mm errors can be found, probably due to the following reasons, 1: bend in X and Y direction of the test course, 2: 
difference of the interior orientation parameters, 3: reading accuracy of the theodolite(«20"), 4: the doll was too small for 
precise extraction of the feature points. 
Considering the above, it is judged that application of the video theodolite System for dynamic analysis of human 
motion is a very useful method. 
5. Conclusion 
Inthis paper the application of a video theodolite Systemfor sports dynamics was described. The results show that 
the unknown parameters, w and x for a sequential image could be estimated as values with vertical and horizontal 
changing values added to w, and «,. w,and x , are the calibration results of the orientation image. Furthermore, it was 
demonstrated that two dimensional coordinates for human feature points in an unknown image could be calculated by 
using the above parameters (w , æ ) and that the other parameters, except w and x, were the same values as in the 
calibration results for the orientation image. But as mentioned above, the camera exposure station for each sequential 
image must be corrected according to the motion of the rotation angles of the theodolite. 
Consequently, utilization of the video theodolite System is expected to become a useful tool in various real time 
photogrammetric field in the future since the rotation parameters can be acquired in real time and thus recorded as a part 
of the image data. There are, however, still some issues which need to be solved before real time photogrammetry can 
become operational, for example calibration without any control or automated recognition of feature points. 
References 
1) H. CHIKATSU, S. MURAI ; Sports Dynamics of Carl Lewis through 100m Race using Video Imagery, 17th International 
Archives of Photogrammetry and Remote Sensing, Vol.29, Part 5, pp.875-879, 1992. 
2) H. CHIKATSU, S. MURAI ; Dynamic Analysis of Boat Rowing using Video Imagery, Journal of the Japan Society. of 
Photogrammetry and Remote Sensing, Vol.32, No.3, pp. 43-49, 1993. 
3)H. CHIKATSU, S. MURAI ; Application of Image Analysis to Rowing Dynamics using Video Camera, Proceeding of the 
Commission V Symposium, Vol.30, Part 5, pp.35-40, 1994. 
IAPRS, Vol. 30, Part 5W1, ISPRS Intercommission Workshop "From Pixels to Sequences", Zurich, March 22-24 1995