Derivation of studio camera position and motion from the camera

Television – Special applications – Object or scene measurement

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348 25, 348700, 348703, H04N 718

Patent

active

055024823

DESCRIPTION:

BRIEF SUMMARY
FIELD OF THE INVENTION

This invention relates to the derivation of information regarding the position of a television camera from image data acquired by the camera.


BACKGROUND TO THE INVENTION

In television production, it is often required to video live action in the studio and electronically superimpose the action on a background image. This is usually done by shooting the action in front of a blue background and generating a `key` from the video signal to distinguish between foreground and background. In the background areas, the chosen background image can be electronically inserted.
One limitation to this technique is that the camera in the studio cannot move, since this would generate motion of the foreground without commensurate background movement. One way of allowing the camera to move is to use a robotic camera mounting that allows a predefined camera motion to be executed, the same camera motion being used when the background images are shot. However the need for predefined motion places severe artistic limitations on the production process.
Techniques are currently under development that aim to be able to generate electronically background images that can be changed as the camera is moved so that they are appropriate to the present camera position. Thus a means of measuring the position of the camera in the studio is required. One way in which this can be done is to attach sensors to the camera to determine its position and angle of view; however the use of such sensors is not always practical.
The problem being addressed here is a method to derive the position and motion of the camera using only the video signal from the camera. Thus it can be used on an unmodified camera without special sensors.


DESCRIPTION OF PRIOR ART

The derivation of the position and motion of a camera by analysis of its image signal is a task often referred to as passive navigation; there are many examples of approaches to this problem in the literature, the more pertinent of which are as follows:
1. Brandt et al. 1990. Recursive motion estimation based on a model of the camera dynamics.
2. Brandt, A., Karmann, K., Lanser, S. Signal Processing V: Theories and Applications (Ed. Torres, L. et al.), Elsevir, pp. 959-962, 1990.
3. Buxton et al 1985 Machine perception of visual motion. Buxton, B. F., Buxton, H., Murray, D. W., Williams, N. S. GEC Journal of Research, Vol. 3 No. 3, pp. 145-161.
4. Netravali and Robbins 1979 Motion-compensated television coding: Part 1. Netravali, A. N., Robbins, J. D. Bell System Technical Journal Vol. 58. No. 3, Mar. 1979, pp. 631-670.
5. Thomas 1987 Television motion measurement for DATV and other applications. Thomas, G. A. BBC Research Department Report No. 1987/11.
6. Uomori et al. 1992 Electronic image stabilisation system for video cameras and VCRs. Uomori, K., Morimura, A., Ishii, J. SMPTE Journal, Vol. 101 No. 2, pp. 66-75, Feb. 1992.
7. Wu and Kittel 1990 Wu, S. F., Kittel, J. 1990. A differential method for simultaneous estimation of rotation, change of scale and translation. Signal Processing: Image Communication 2, Elsevier, 1990, pp. 69-80.
For example, if a number of feature points can be identified in the image and their motion tracked from frame to frame, it is possible to calculate the motion of the camera relative to these points by solving a number of non-linear simultaneous equations Buxton et al. 1985!. The tracking of feature points is often achieved by measuring the optical flow (motion) field of the image. This can be done in a number of ways, for example by using an algorithm based on measurements of the spariotemporal luminanee gradient of the image Netraveli and Robbins 1979!.
A similar method is to use Kalman filtering techniques to estimate the camera motion parameters from the optical flow field and depth information Brandt et al; 1990!.
However, in order to obtain reliable (relatively noise-free) information relating to the motion of the camera, it is necessary to have a good number of feature points visible at all times, and for these to be distributed in

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S. F. Wu, et al., "A Differential Method for Simultaneous Estimation of Rotation, Change of Scale and Translation", Signal Processing: Image Communication 2 (1990), pp. 69-80.
K. Uomori et al., "Electronic Image Stabilization System for Video Cameras and VCRs", SMPTE Journal, Feb. 1992, No. 2, pp. 66-75.
A. N. Netravali et al., "Motion-Compensated Television Coding: Part I", The Bell System Technical Journal, vol. 58, No. 3, Mar. 1979, pp. 631-671.
B. F. Buxton et al., "Machine Perception of Visual Motion", GEC Journal of Research, vol. 3, No. 3, 1985, pp. 145-161.
A. V. Brandt, et al., "Recursive Motion Estimation Based on a Model of the Camera Dynamics", Signal Processing V: Theories and Applications, 1990, pp. 959-962.
G. A. Thomas, B. A., "Television Motion Measurement for Datv and Other Applications", The British Broadcasting Corporation, Research Department, Report No. 1987/11, Engineering Division, Sep. 1987, pp. 1-20.
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Rose, "Evaluation of a Motion Estimation Procedure for Low-Frame-Rate Aerial Images", ISCAS'88 Journal, 1988 IEEE International Symposium on Circuits and Systems vol. 3 of 3, pp. 2309-2312.

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