Method and system for processing image data

1. A method for processing image data representing a segmentation mask, wherein the image data are generated from a sequence of images, comprising:

generating two-dimensional shape representations of a three-dimensional object on the basis of a plurality of parameter sets;

matching motion blocks of the segmentation mask with the two-dimensional shape representations to obtain a best fit parameter set;

segmenting one of the images into a plurality of segments; and

applying a scaling factor to the image data that are disposed in a specific segment of the image, wherein different scaling factors are assigned to different segments of the image.

2. The method of claim 1 , further comprising:

determining a distance between the three-dimensional object and a camera position from the best fit parameter set.

3. The method of claim 1 , wherein the parameter set comprises distance and perspective of a camera, that has generated the image data, with respect to the three-dimensional object.

4. The method of claim 1 , wherein the segmentation mask is generated from a sequence of images by a method comprising:

partitioning each image of the sequence of images into blocks;

identifying a moving block;

determining direction and distance of movement of the moving block;

grouping adjacent moving blocks with directions and distances within predetermined intervals to form motion blocks.

5. The method of claim 4 , wherein moving blocks are identified by supplying image data of the sequence of images concurrently to

a first motion estimator, the first motion estimator being adapted to identify moving items which have performed a movement between consecutive images of a first sequence, the first sequence having a first frame rate; and

a second motion estimator, the second motion estimator being adapted to identify moving items which have performed a movement between consecutive images of a second sequence, the second sequence having a second frame rate.

6. The method of claim 1 , wherein the segments are disposed along one axis.

7. The method of claim 1 , wherein the segments are disposed along two axes, the two axes being orthogonal to each other.

8. The method of claim 1 , wherein the scaling factor decreases from a value larger than 1 to a value smaller than 1 along an axis.

9. The method of claim 1 , wherein the image data are generated from a sequence of images, the method further comprising supplying image data of the sequence of images concurrently to

a first motion estimator, the first motion estimator being adapted to identify moving blocks which have performed a movement between consecutive images of a first sequence, the first sequence having a first frame rate; and

a second motion estimator, the second motion estimator being adapted to identify moving blocks which have performed a movement between consecutive images of a second sequence, the second sequence having a second frame rate.

10. The method of claim 9 , wherein the first frame rate is a multiple integer of the second frame rate.

11. The method of claim 1 , further comprising:

detecting a front most object from the motion block; and

subtracting the front most object from the motion block.

12. A method for detecting a moving object, comprising

generating image data by taking a sequence of images; and

performing the method of claim 1 .

13. A non-transitory computer readable medium having stored thereon a computer program that when executed by a computer causes the computer to implement the method according to claim 1 and the steps thereof when it is carried out on a data processing device.

14. A system for processing image data representing a segmentation mask, wherein the image data are generated from a sequence of images, the system comprising components that are configured

to generate two-dimensional shape representations of a three-dimensional object on the basis of a plurality of parameter sets;

to match motion blocks of the segmentation mask with the two-dimensional shape representations to obtain a best fit parameter set;

to segment one of the images into a plurality of segments; and

to apply a scaling factor to the image data that are disposed in a specific segment of the image, wherein different scaling factors are assigned to different segments of the image.

15. The system of claim 14 , the system further comprising a component that is adapted to determine a distance between the three-dimensional object and a camera position.

16. The system of claim 14 , wherein the image data are generated from a sequence of images, the system further comprising

a first motion estimator, the first motion estimator being adapted to identify moving blocks which have performed a movement between consecutive images of a first sequence, the first sequence having a first frame rate; and

a second motion estimator, the second motion estimator being adapted to identify moving blocks which have performed a movement between consecutive images of a second sequence, the second sequence having a second frame rate,

the first and the second motion estimators being disposed in such a manner that the image data may be concurrently fed to the first and second motion estimators.

17. The system of claim 14 , further comprising components that are adapted

to detect a front most object from the motion block; and

to subtract the front most object from the motion block.

18. A system for detecting a moving object, comprising

a device that is adapted to generate image data by taking a sequence of images; and

the system of claim 14 .