1. A method of forming a first strained semiconductor layer over an insulating layer comprising the steps of:
forming a stress-providing layer over a structure comprising a first semiconductor layer, said first semiconductor layer is located atop an insulating layer;
patterning said stress-providing layer and said first semiconductor layer into at least one island;
heating the structure containing said at least one island to a temperature that causes strain transfer from the stress-providing layer to the first semiconductor layer; and
removing the stress-providing layer to form a first strained semiconductor island layer directly atop said insulating layer.
2. The method of claim 1 wherein said first semiconductor layer and said insulating layer are components of a preformed silicon-on-insulator substrate.
3. The method of claim 2 wherein said preformed silicon-on-insulator substrate is fabricated by separation by ion implantation of oxygen or a layer transfer process.
4. The method of claim 1 wherein at least one implantation step is performed between said forming and patterning step.
5. The method of claim 4 wherein said at least one implantation step comprises implanting a dopant species into at least said insulating layer.
6. The method of claim 5 wherein said dopant species is boron.
7. The method of claim 4 wherein said at least one implantation step comprises implanting an energetic ion at, or near, an interface formed between the first semiconductor layer and the insulating layer.
8. The method of claim 7 wherein said energetic ion comprises hydrogen, deuterium, helium, oxygen, neon or mixtures and isotopes thereof.
9. The method of claim 7 wherein said energetic ion is a hydrogen ion.
10. The method of claim 1 wherein said patterning comprises lithography and etching.
11. The method of claim 1 wherein said first semiconductor layer comprises Si, SiC, SiGe, SiGeC, Ge, GaAs, InAs or InP.
12. The method of claim 1 wherein said stress-providing layer comprises a Ge-containing layer, a silicon nitride layer, a silicon carbide layer, a silicate glass or mixtures thereof.
13. The method of claim 1 wherein said heating step is performed at a temperature that causes the insulating layer to have a visco-elastic property.
14. The method of claim 13 wherein said heating is performed at a temperature that is about 900\xb0 C. or greater.
15. The method of claim 1 wherein said first strained semiconductor layer has a tensile strain.
16. The method of claim 1 wherein said first strained semiconductor layer has a compressive strain.
17. The method of claim 1 further comprising forming a second island having a second stress-providing layer that has a different stress then the stress in said stress-providing layer.
18. The method of claim 1 wherein said first semiconductor layer comprises IIIV or IIVI compound semiconductor, where II, III, V and VI represents groups from the Periodic Table of Elements.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A method of simultaneous tracking of multiple objects in a sequence of video frames captured by multiple cameras comprising:
extracting a foreground image from a background image in a frame;
segmenting objects from the foreground image;
tracking objects within the frame by identifying the largest connected components inside each objects region of interest;
globally tracking positions of objects over time across multiple frames;
fusing track data of objects obtained from multiple cameras to infer object positions; and
resolving conflicts to estimate most likely object positions over time.
2. The method of claim 1, wherein segmenting the objects from the foreground image comprises segmenting the objects from the foreground image by examining motion of the objects in the sequence of video frames.
3. The method of claim 2, wherein examining motion of the objects comprises using a two tier hierarchical median filter.
4. The method of claim 3, wherein segmenting objects from the foreground image comprises segmenting objects from the foreground image under varying illuminations of the foreground image and the objects.
5. The method of claim 3, wherein segmenting objects comprises computing a difference between a current frame and a field model to produce a difference image, applying a field template to clip a region of interest from the difference image to produce a clipped difference image, and enhancing the clipped difference image to produce an object image.
6. The method of claim 1, wherein globally tracking positions of objects over time comprises using a sequential Monte Carlo technique.
7. The method of claim 1, wherein fusing track data of objects comprises disambiguating disparities due to occlusion of objects.
8. The method of claim 1, wherein the foreground image comprises a playing field for a sporting event and the objects comprise players participating in the sporting event.
9. The method of claim 1, further comprising initializing object tracking processing by creating a foreground image template, calibrating the cameras, and identifying visible objects on a first frame.
10. An article comprising: a storage medium having a plurality of machine accessible instructions, wherein when the instructions are executed by a processor, the instructions provide for simultaneous tracking of multiple objects in a sequence of video frames captured by multiple cameras by
extracting a foreground image from a background image in a frame;
segmenting objects from the foreground image;
tracking objects within the frame by identifying the largest connected components inside each object’s region of interest;
globally tracking positions of objects over time across multiple frames;
fusing track data of objects obtained from multiple cameras to infer object positions; and
resolving conflicts to estimate most likely object positions over time.
11. The article of claim 10, wherein instructions for segmenting the objects from the foreground image comprise instructions for segmenting the objects from the foreground image by examining motion of the objects in the sequence of video frames.
12. The article of claim 11, wherein instructions for examining motion of the objects comprise instructions for implementing a two tier hierarchical median filter.
13. The article of claim 12, wherein instructions for segmenting objects from the foreground image comprise instructions for segmenting objects from the foreground image under varying illuminations of the foreground image and the objects.
14. The article of claim 12, wherein instructions for segmenting objects comprise instructions for computing a difference between a current frame and a field model to produce a difference image, applying a field template to clip a region of interest from the difference image to produce a clipped difference image, and enhancing the clipped difference image to produce an object image.
15. The article of claim 10, wherein instructions for globally tracking positions of objects over time comprise instructions implementing a sequential Monte Carlo technique.
16. The article of claim 10, wherein instructions for fusing track data of objects comprise instructions for disambiguating disparities due to occlusion of objects.
17. The article of claim 10, wherein the foreground image comprises a playing field for a sporting event and the objects comprise players participating in the sporting event.
18. The article of claim 10, further comprising instructions for initializing object tracking processing by creating a foreground image template, calibrating the cameras, and identifying visible objects on a first frame.
19. A system for simultaneous tracking of multiple objects in a three dimensional physical scene by analysis of a sequence of video frames comprising:
a plurality of video cameras to generate a plurality of sequences of video frames representing the scene over time; and
a processing system having at least one processor to simultaneously track the multiple objects, the processing system comprising
a field model generator component to extract a foreground image from a background image in a frame;
a segmentation component to segment objects from the foreground image;
a tracking component to track objects within the frame by identifying the largest connected components inside each object’s region of interest and to globally track positions of objects over time across multiple frames; and
a data fusion component to fuse track data of objects obtained from the plurality of video cameras to infer object positions, and to resolve conflicts to estimate most likely object positions over time.
20. The system of claim 19, wherein the segmentation component segments the objects from the foreground image by examining motion of the objects in the sequence of video frames.
21. The system of claim 20, wherein the segmentation component examines motion of the objects using a two tier hierarchical median filter.
22. The system of claim 21, wherein the segmentation component segments objects from the foreground image under varying illuminations of the foreground image and the objects.
23. The system of claim 21, wherein the segmentation component computes a difference between a current frame and a field model to produce a difference image, applies a field template to clip a region of interest from the difference image to produce a clipped difference image, and enhances the clipped difference image to produce an object image.
24. The system of claim 19, wherein the tracking component globally tracks positions of objects over time using a sequential Monte Carlo technique.
25. The system of claim 19, wherein the data fusion component disambiguates disparities due to occlusion of objects.
26. The system of claim 19, further comprising an initialization component to initialize object tracking processing by creating a foreground image template, calibrating the cameras, and identifying visible objects on a first frame.