Photography – With exposure objective focusing means – focusing aid – or... – Processing circuit
Reexamination Certificate
2000-04-13
2001-10-09
Rutledge, D. (Department: 2851)
Photography
With exposure objective focusing means, focusing aid, or...
Processing circuit
C396S429000, C348S229100, C348S236000
Reexamination Certificate
active
06301440
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention generally relates to expert systems applied to computer image processing, and more particularly to computer image processing for automatically adjusting the controls of a camera according to the object framed by the user. The camera may be a still camera or a video camera.
2. Background Description Electronic cameras are sophisticated devices with various controls for affecting the manner in which a photograph is taken. Traditional electronic cameras have limited controls for adjusting focus, aperture, shutter speed and, in some cases, lens focal length. Later-generation cameras are more sophisticated, adjusting parameters that include focus point for an auto-focus camera, meter weighting for exposure control, f-stop correction, depth-of-field, electronic flash parameters, number of exposures composing a given image, and more.
In spite of their increased functionality, conventional cameras as discussed above have significant drawbacks. These cameras, for example, require a user to exert an overwhelming degree of control over the picture-taking process in terms of correctly setting the camera parameters. This usually proves too great a task for the amateur photographer. As a result, photographs are often taken with inappropriate settings and thus tend to be of poor quality. For the novice user especially, such sophistication is too intimidating. Even when the camera controls are hidden, either in simple cameras or in simple modes where everything is automatic, poor photographs may still result because the user does not have the knowledge of photography or the control to compensate for backlighting, to set the depth-of-field appropriately, and the like.
Previous attempts to solve these problems involved automating functions or abstracting parameters into a different space. Auto-focus, automatic exposure (e.g., U.S. Pat. No. 5,860,039 to Kusumoto Keiji) and depth-of-field selection are all attempts at simplification, but in some ways they have added to the problem of overwhelming complexity instead of helping to solve it. Let us take auto focus as an example. Earlier cameras needed to be manually focused. Modern cameras, however, are almost always auto-focused. However, in such simplified cameras where the focus control is removed from the user, there is no simple way to specify which object in the scene should be focused upon, resulting in pictures where an off-center subject is out of focus. Sophisticated cameras tackle this problem by reintroducing some complexity —a focus lock button, or manual selection of the focus point. There is still, however, a control for focus; it is just specified in a different manner.
In particular domains of photography, special sets of parameters will be chosen. For sports photography, high speeds are necessary. For close-up images, the depth-of-field needs to be controlled well. For night photography, a flash must be used. An expert photographer will have a good knowledge of how to control the camera for many of these settings. Previous attempts have been made to encapsulate this knowledge in modules (such as used by Minolta cameras), but the expert still needs to know which module is the most appropriate for a situation, be in possession of the correct module, insert it in the camera, adjust the parameters of the module and so forth.
In view of the foregoing considerations, it is clear that cameras in existence today have complex controls which, at best, are burdensome to their users and result in photographs being taken of non-optimal quality. A need therefore exists for an automatic system and method, implemented preferably in highly sophisticated electronic cameras, which either automatically sets camera parameters at optimal settings and/or which gives the user the ability to set those parameters in an easy and efficient manner as compared with conventional devices.
SUMMARY OF THE INVENTION
It is therefore an object of the present invention to provide an improved system and method for setting the parameters for an image acquisition device of a camera.
This and other objects of the invention are achieved by providing a system and method which analyzes an image to be taken in the same manner as an expert photographer would and then sets the image acquisition parameters according to a derived class of the subject matter. According to the invention, a temporary image acquisition unit acquires a temporary image, a scene analysis unit extracts information from the temporary image and generates at least one scene hypothesis from the extracted information, a photographic expert unit adjusts image capture parameters based on the scene hypothesis, and a permanent image acquisition unit acquires a permanent image based on the image capture parameters adjusted by the photographic expert unit. The extracted information may include at least one of image features, scene components, classifications, or imaging parameters. The image capture may include one or more of the following: focus distance, aperture, shutter speed, zoom, filter application, filter parameters and imager sensitivity.
In one embodiment, the temporary image acquisition unit and permanent image acquisition unit may be the same unit. Advantageously, the system can run in a fully automatic mode choosing the best image parameters, or a “guided mode” where the user is prompted with choices where a number of alternate settings would be reasonable. Also, mapping between input characteristics and image parameters may be learned automatically by the photographic expert unit observing settings input by the user for different kinds of images.
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Flickner, et al., Query by Image and Video Content: The QBIC System, IEEE Computer, vol. 28, No. 9, Sep. 1995.*
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D. Cowell, Probabilistic Networks & Expert Systems, Springer, 1999 XII, 321, pp. 45.
Bolle Rudolf M.
Connell Jonathan H.
Hampapur Arun
Senior Andrew W.
International Business Machines Corp.
McGuireWoods LLP
Percello Louis J.
Rutledge D.
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