Studio camera position and motion may be derived from the camera image by separating out the background and deriving from a background having a number of areas of hue and/or brightness different from adjacent areas estimates of movement from one image to the next. The initial image is used as a reference and amended with predicted motion value. The amended image is compared with incoming images and the result used to derive translation and scale change information. Once the proportion of the reference image contained in an incoming image falls below a threshold a fresh reference image is adopted.
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0. 38. A method of deriving a measure of translation and scale change from a camera output signal, the method comprising:
providing a background with a pattern comprising a plurality of areas of a first tone and a plurality of areas of a second tone arranged so that transitions between areas occur along at least two axes, whereby the transitions provide reference points from which measures of both translation and scale change may be determined; receiving said camera output signal defining a camera image from a camera viewing a scene containing at least a portion of said background; detecting said first and second tones in the camera output signal by chroma-keying; and deriving from results of said detecting step a measure of translation and scale change.
0. 57. Apparatus for deriving at least one parameter representing the movement of a camera from a camera image, said camera viewing at least a portion of a background having a pattern comprising a plurality of areas of a first tone and a plurality of areas of a second tone arranged so that transitions between areas occur along at least two axes, whereby the transitions provide reference points from which measures of both translation and scale change may be determined, the apparatus comprising:
means for receiving an output signal from said camera, said signal defining a camera image; means for detecting said first and second tones in the camera image by chroma-keying; and means for deriving from results of said detecting means a measure of translation and scale change.
0. 77. Apparatus for deriving at least one parameter representing the movement of a camera from a camera image, said camera viewing at least a portion of a background having a pattern comprising a plurality of areas of a first tone and a plurality of areas of a second tone arranged so that transitions between areas occur along at least two axes, whereby the transitions provide reference points from which measures of both translation and scale change may be determined, the apparatus comprising:
an input receiving an output signal from said camera, said signal defining a camera image; and a signal processing system that 1 ) detects said first and second tones in the camera image by chroma-keying; and 2 16. Apparatus for measuring the translation and scale change in a sequence of video images, comprising:
means for acquiring said sequence of images; storage means for storing a first image in said sequence to form a stored image; means for forming a prediction of the translation and scale change from said stored image to a further image in said sequence; means for comparing said stored image to said further image by transforming at least one of said stored image by and said further image based on said prediction of the translation and scale change to form a transformed first image; means for comparing said transformed first image with a further image in the sequence ; means for deriving measurements of translation and scale change between said stored image and said further image from said comparison and said prediction; and means for replacing said first image with a new incoming image when the image area common to both said first image and incoming image falls below a given proportion of the whole image area of said incoming images.
0. 31. Apparatus for measuring the translation and scale change in a sequence of video images, comprising:
an image storage unit that stores a first image in said sequence to form a stored image; a prediction unit that forms a prediction of the translation and scale change from said stored image to a further image in said sequence; an image transformer that compares said stored image to said further image by transforming at least one of said stored image and said further image based on said prediction of the translation and scale change; a measurement unit that derives measurements of translation and scale change between said stored image and said further image from said comparison and said prediction; and a refresh signal generator that replaces said first image with a new incoming image when the image area common to both said first image and incoming image falls below a given proportion of the whole image area of said incoming images.
1. A method of measuring the translation and scale change in a sequence of video images, the method comprising:
storing a first image in said sequence to form a stored image; forming a prediction of the translation and scale change from said stored image to a further image in said sequence; comparing said stored image to said further image by transforming at least one of said stored image by and said further image based on said prediction of the translation and scale change; to form a transformed first image; comparing a further image in said sequence with said transformed first image; deriving measurements of translation and scale change between said stored image and said further image from said comparison and said prediction; and replacing said first image with a new incoming image when the image area common to both said first image and incoming image falls below a given proportion of the whole image area of said incoming image.
0. 35. Apparatus for measuring the translation and scale change in a sequence of video images derived by a camera, comprising:
an image storage unit that stores a first image of said sequence to form a stored image, said image comprising a single component signal derived by a camera viewing a scene containing a background of near-uniform color, said background being divided into a plurality of areas each having a hue and/or brightness different from the hue and/or brightness of adjacent areas to allow generation of a key signal by chroma-key techniques; a signal former that forms said single-component signal from said camera signal so as to accentuate differences in hue and/or brightness of individual areas of the background to enable motion estimation; a prediction unit that forms a prediction of the translation and scale change from said stored image to a further image in said sequence; an image transformer that compares said stored image to said further image by transforming at least one of the stored image and said further image based on said prediction of the translation and scale change; and a measurement unit that derives, from said comparison and said prediction, measurements of translation of scale change between said stored image and said further image.
6. A method of measuring the translation and scale change in a sequence of video images of a camera signal derived by a camera, comprising:
storing a first image of said sequence to form a stored image said image comprising a single component signal derived by a camera viewing a scene containing a background of near-uniform color, and said background being divided into a plurality of areas each having a hue and/or brightness different from the hue and/or brightness of adjacent areas to allow generation of a key signal by chroma-key techniques; forming said single-component signal from said camera signal so as to accentuate differences in hue and/or brightness of individual areas of the background to enable motion estimation; forming a prediction of the translation and scale change from said stored image to a further image in said sequence; comparing said stored image to said further image by transforming at least one of said stored image by and said further image based on said prediction of the translation and scale change; to form a transformed first image; comparing a further image in said sequence with said transformed first image; and deriving measurements of translation and scale change between said stored image and said further image from said comparison and said prediction.
20. Apparatus for measuring the translation and scale change in a sequence of video images derived by a camera, comprising:
means for storing a first image of said sequence to form a stored image, said image comprising a single component signal derived by a camera viewing a scene containing a background of near-uniform color, said background being divided into a plurality of areas each having a hue and/or brightness different from the hue and/or brightness of adjacent areas to allow generation of a key signal by chroma-key techniques; means for forming said single-component signal from said camera signal so as to accentuate differences in hue and/or brightness of individual areas of the background to enable motion estimation; means for forming a prediction of the translation and scale change from said stored image to a further image in said sequence; means for comparing said stored image to said further image by transforming at least one of the stored image by a and said further image based on said prediction of the translation and scale change to form a transformed first image; means for comparing a further image in said sequence with said transformed first image; and means for deriving, from said comparison and said prediction, measurements of translation of scale change between said stored image and said further image.
2. The method of
3. The method of
4. The method of
5. The method of
each image is a single-component signal derived from a camera viewing a scene containing a background of near-uniform color; said background is divided into a plurality of areas each having a hue and/or brightness different from the hue and/or brightness of adjacent areas to allow the generation of a key signal by chroma-key techniques; and wherein said single-component signal is formed from a three-component camera signal so to accentuate differences in hue and/or brightness of individual areas of said background to enable motion estimation.
7. The method of
9. The method of
10. The method of
selecting a number of measurement points in said first image for motion estimation; and replacing said first image with a new incoming image when the number of measurement points which lie in areas of background visible in both said first image and a given incoming image falls below a given proportion of the total number of measurement points.
11. The method of
12. The method of
14. The method of
17. The apparatus of
18. The apparatus of
19. The apparatus of
means for generating a single-component signal from a camera viewing a scene containing a background of near-uniform color, said background being divided into a plurality of areas each having a hue and/or brightness different from the hue and/or brightness of adjacent areas to allow the generation of a key signal by chroma-key techniques, and wherein the single-component signal is formed from a three-component camera signal so as to accentuate differences in hue and/or brightness of individual areas of the background to enable motion estimation.
21. The apparatus of
23. The apparatus of
means for predicting the translation and scale change by the computation of a number of simultaneous equations each of which relate the translation and scale change to spatial and temporal gradients at a point in the first image and which are solved to yield a least-squares solution for the motion parameters.
24. The apparatus of
means for selecting a number of measurement points in the first image for motion estimation and for replacing the first image with a new incoming image when the number of measurement points which lie in areas of background visible in both the first image and a given incoming image falls below a given proportion of the total number of measurement points.
25. The apparatus of
26. The apparatus of
0. 27. The method of
transforming said stored image by said prediction of the translation and scale change to form a transformed first image; and comparing a further image in said sequence with said transformed first image.
0. 28. The method of
transforming said stored image by said prediction of the translation and scale change to form a transformed first image; and comparing a further image in said sequence with said transformed first image.
0. 29. The apparatus of
means for transforming said stored image by said prediction of the translation and scale change to form a transformed first image; and means for comparing a further image in said sequence with said transformed first image.
0. 30. The apparatus of
means for transforming said stored image by said prediction of the translation and scale change to form a transformed first image; and means for comparing a further image in said sequence with said transformed first image.
0. 32. The apparatus of
0. 33. The apparatus of
0. 34. The apparatus of
means for generating a single-component signal from a camera viewing a scene containing a background of near-uniform color, said background being divided into a plurality of areas each having a hue and/or brightness different from the hue and/or brightness of adjacent areas to allow the generation of a key signal by chroma-key techniques, and wherein the single-component signal is formed from a three-component camera signal so as to accentuate differences in hue and/or brightness of individual areas of the background to enable motion estimation.
0. 36. The apparatus of
0. 37. The apparatus of
0. 39. A method according to
0. 40. A method according to
0. 41. A method according to
0. 42. A method according to
0. 43. A method according to
0. 44. A method according to
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0. 51. A method according to
0. 52. A method according to
0. 53. A method according to
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0. 56. A method according to
0. 58. Apparatus according to
0. 59. Apparatus according to
0. 60. Apparatus according to
0. 61. Apparatus according to
0. 62. Apparatus according to
0. 63. Apparatus according to
0. 64. Apparatus according to
0. 65. Apparatus according to
0. 66. Apparatus according to
0. 67. Apparatus according to claims 57, further comprising an image store that stores a reference image for use by said deriving means.
0. 68. Apparatus according to
0. 69. Apparatus according to
0. 70. Apparatus according to
0. 71. Apparatus according to claims 67 wherein the stored reference image is replaced when the accumulated translation and scale change exceeds a given threshold.
0. 72. Apparatus according to
0. 73. Apparatus according to
0. 74. Apparatus according to
0. 75. Apparatus according to
0. 76. Apparatus according to
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This invention relates to the derivation of information regarding the position of a television camera from image data acquired by the camera.
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.
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:
The algorithm chosen for measuring global translation and scale change must satisfy the following criteria:
1. The chosen algorithm cannot be too computationally intensive, since it must run in real-time;
2. It must be capable of highly accurate measurements, since measurement errors will manifest themselves as displacement errors between foreground and background;
3. Measurement errors should not accumulate to a significant extent as the camera moves further away from its starting point.
Embodiment: Motion Estimation Followed by Global Motion Parameter Determination
An example of one type of algorithm that could be used is one based on a recursive spario-temporal gradient technique described in reference 4 [Netravali and Robbins 1979]. This kind of algorithm is known to be computationally efficient and to be able to measure small displacements to a high accuracy. Other algorithms based on block matching described in reference 6 [Uomori et al. 1992] or phase correlation described in reference 5 [Thomas 1987] may also be suitable.
The algorithm may be used to estimate the motion on a sample-by-sample basis between each new camera image and a stored reference image. The reference image is initially that viewed by the camera at the start of the shooting, when the camera is in a known position. Before each measurement, the expected translation and scale change is predicted from previous measurements and the reference image is subject to a translation and scale change by this estimated amount. Thus the motion estimation process need only measure the difference between the actual and predicted motion.
The motion vector field produced is analyzed to determine the horizontal and vertical displacement and scale change. This can be done by selecting a number of points in the vector field likely to have accurate vectors (for example in regions having both high image detail and uniform vectors). The scale change can be determined by examining the difference between selected vectors as a function of the spatial separation of the points. The translation can then be determined from the average values of the measured vectors after discounting the effect of the scale change. The measured values are added to the estimated values to yield the accumulated displacement and scale change for the present camera image.
More sophisticated methods of analysing the vector field could be added in future, for example in conjunction with means for determining the depth of given image points, to extend the flexibility of the system.
As the accumulated translation and scale change get larger, the translated reference image will begin to provide a poor approximation to the current camera image. For example, if the camera is panning to the right, picture material on the right of the current image will not be present in the reference image and so no motion estimate can be obtained for this area. To alleviate this problem, once the accumulated values exceed a given threshold the reference image is replaced by the present camera image. Each time this happens however, measurement errors will accumulate.
All the processing will be carried out on images that have been spatially filtered and subsampled. This will reduce the amount of computation required, with no significant loss in measurement accuracy. The filtering process also softens the image; this is known to improve the accuracy and reliability of gradient-type motion estimators. Further computational savings can be achieved by carrying out the processing between alternate fields rather than for every field; this will reduce the accuracy with which rapid acceleration can be tracked but this is unlikely to be a problem since most movements of studio cameras tend to be smooth.
Software to implement the most computationally-intensive pans of the processing has been written and benchmarked, to provide information to aid the specification and design of the hardware accelerator. The benchmarks showed that the process of filtering and down-sampling the incoming images is likely to use over half of the total computation time.
Embodiment 2: Direct Estimation of Global Motion Parameters An alternative and preferred method of determining global translation and scale change is to derive them directly from the video signal. A method of doing this is described in reference 7 by [Wu and Kittel Kittler 1990]. We have extended this method to work using a stored reference image and to use the predicted motion values as a staging point. Furthermore, the technique is applied only at a sub-set of pixels in the image, that we have termed measurement points, in order to reduce the computational load. As in the previous embodiment the RGB video signal is matrixed to form a single-component signal and spatially low-pass filtered prior to processing. As described previously, only areas identified by a key signal as background are considered.
The method is applied by considering a number of measurement points in each incoming image and the corresponding points in the reference image, displaced according to the predicted translation and scale change. These predicted values may be calculated, for example, by linear extrapolation of the measurements made in the preceding two images. The measurement points may be arranged as a regular array, as shown in
At each measurement point, luminance gradients are calculated as shown in FIG. 3. These may be calculated, for example, by simply taking the difference between pixels either side of the measurement point. Spatial gradients are also calculated for the corresponding point in the reference image, offset by the predicted motion. Sub-pixel interpolation may be employed when calculating these values. The temporal luminance gradient is also calculated; again sub-pixel interpolation may be used in the reference image. An equation is formed relating the measured gradients to the motion values as follows:
Gradients are (approximately) related to displacement and scale changes by the equation
where
gx=(grx+gcx)/2
gy=(gry+gcy)/2
are the horizontal and vertical luminance gradients averaged between the two images:
gcx, gcy are horizontal and vertical luminance gradients in current image;
grx, gry are horizontal and vertical luminance gradients in reference image; and
gt is the temporal luminance gradient.
X and Y are the displacements between current and reference image and Z is the scale change (over and above those predicted).
An equation is formed for each measurement point and a least-squares solution is calculated to obtain values for X, Y, and Z.
Derivation of the equation may be found in reference 7 [ Wu and Kinel 1990] Kittler (this reference includes the effect of image rotation; we have omitted rotation since it is of little relevance here as studio cameras tend to be mounted such that they cannot rotate about the optic axis).
The set of simultaneous linear equations derived in this way (one for each measurement point) is solved using a standard least-squares solution method to yield estimates of the difference between the predicted and the actual translation and scale change. The calculated translation values are then added to the predicted values to yield the estimated translation between the reference image and the current image.
Similarly, the calculated and predicted scale changes are multiplied together to yield the estimated scale change. The estimated values thus calculated are then used to derive a prediction for the translation and scale change of the following image.
As described earlier, the reference image is updated when the camera has moved sufficiently far away from its initial position. This automatic refreshing process may be triggered, for example, when the area of overlap between the incoming and reference image goes below a given threshold. When assessing the area of overlap, the key signal needs to be taken account of, since for example an actor who obscured the left half of the background in the reference image might move so that he obscures the right half, leaving no visible background in common between incoming and reference images. One way of measuring the degree of overlap is to count the number of measurement points that are usable (ie. that fall in visible background areas of both the incoming and reference image). This number may be divided by the number of measurement points that were usable when the reference image was first used to obtain a measure of the usable image area as a fraction of the maximum area obtainable with that reference image. If the initial number of usable points in a given reference image was itself below a given threshold, this would indicate that most of the image was taken up with foreground rather than background, and a warning message should be produced.
It can also be advantageous to refresh the reference image if the measured scale change exceeds a given range (eg, if the camera zooms in a long way). Although in this situation the number of usable measurement points may be very high, the resolution of the stored reference image could become inadequate to allow accurate motion estimation.
When the reference image is updated, it can be retained in memory for future use, together with details of its accumulated displacement and scale change. When a decision is made that the current reference image is no longer appropriate, the stored images can be examined to see whether any of these gave a suitable view of the scene. This assessment can be carried out using similar criteria to those explained above. For example, if the camera pans to the left and then back to its starting position, the initial reference image may be re-used as the camera approachis this position. This ensures the measurements of camera orientation made at the end of the sequence will be as accurate as those made at the beginning.
Referring back to
Although the colour blue is the most common for the backcloth other colours, for example, green or orange are sometimes used when appropriate. The technique described is not peculiar to any particular background colour but requires a slight variation in hue and/or brightness between a number of different areas of the background, and that the areas adjacent to a given area have a brightness and/or hue different from that of the given area. This contrast enables motion estimation from the background to be performed.
Red, green and blue (RGB) colour signals formed by the camera are matrixed into a single colour signal and applied to a spatial low-pass filer (at 14). The low-pass output is applied to an image store 16 which holds the reference image data and whose output is transformed at 18 by applying the predicted motion for the image. The motion adjusted reference image data is applied, together with the low-pass filtered image to a unit 20 which measures the net motion in background areas between an incoming image at input I and a stored reference image at input R. The unit 20 applies one of the motion estimation algorithms described. The net motion measurement is performed under the control of a key signal K derived by a key generator 22 from the unfiltered RGB output from the camera 10 to exclude foreground portions of the image from the measurement. The motion prediction signal is updated on the basis of previous measured motion thus ensuring that the output from the image store 16 is accurately interpolated. When, as discussed previously, the camera has moved sufficiently away from its initial position a refresh signal 24 is sent from the net motion measurement unit 20 to the image store 16. On receipt of the refresh signal 24 a fresh image is stored in the image store and used as the basis for future net motion measurements.
The output from the net motion measurement unit 20 is used to derive an indication of current camera position and orientation as discussed previously.
Optionally, sensors 26 mounted on the camera can provide data to the net motion measurement unit 20 which augment or replace the image-derived motion signal.
The image store 16 may comprise a multi-frame store enabling storage of previous reference images as well as the current reference image.
The technique described can also be applied to image signals showing arbitrary picture material instead of just the blue background described earlier. If objects are moving in the scene, these can be segmented out by virtue of their motion rather than by using a chroma-key signal. The segmentation could be performed, for example, by discounting any measurement points for which the temporal luminance gradient (after compensating for the predicted background motion) was above a certain threshold. More sophisticated techniques for detecting motion relative to the predicted background motion can also be used.
It will be understood that the techniques described may be implemented either by special purpose digital signal processing equipment, by software in a computer, or by a combination of these methods. It will also be clear that the technique can be applied equally well to any television standard.
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