RASTER SCANNING FOR DEPTH DETECTION

• US 20110228251A1
• Filed: 03/17/2010
• Published: 09/22/2011
• Est. Priority Date: 03/17/2010
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Lutian, John, Yee, Dawson
• Granted Patent: US 8,279,418 B2
• Time in Patent Office: Days
• US Class Current: 356/5.01
• CPC Class Codes: G01C 3/08 Use of electric radiation detectors
• CPC Class Codes: G01S 17/10 using transmission of interrupted, pulse-modulated waves determination of distance by phase measurements G01S17/32
• CPC Class Codes: G01S 17/36 with phase comparison between the received signal and the contemporaneously transmitted signal
• CPC Class Codes: G01S 17/42 Simultaneous measurement of distance and other co-ordinates indirect measurement G01S17/46
• CPC Class Codes: G01S 17/48 Active triangulation systems, i.e. using the transmission and reflection of electromagnetic waves other than radio waves
• CPC Class Codes: G01S 17/66 Tracking systems using electromagnetic waves other than radio waves
• CPC Class Codes: G01S 17/88 Lidar systems specially adapted for specific applications
• CPC Class Codes: G01S 17/89 for mapping or imaging
• CPC Class Codes: G01S 7/4817 relating to scanning
• CPC Class Codes: G06T 2207/30196 Human being; Person
• CPC Class Codes: G06T 7/521 from laser ranging, e.g. using interferometry; from the projection of structured light

Abstract

Techniques are provided for determining distance to an object in a depth camera'"'"'s field of view. The techniques may include raster scanning light over the object and detecting reflected light from the object. One or more distances to the object may be determined based on the reflected image. A 3D mapping of the object may be generated. The distance(s) to the object may be determined based on times-of-flight between transmitting the light from a light source in the camera to receiving the reflected image from the object. Raster scanning the light may include raster scanning a pattern into the field of view. Determining the distance(s) to the object may include determining spatial differences between a reflected image of the pattern that is received at the camera and a reference pattern.

Claims

9. A depth camera, comprising:

a light source that transmits light;

a scanning element in optical communication with the light source, the scanning element scans the light over a field of view by scanning in an x-direction and a y-direction;

a light detector that receives a reflected image of the scanned light from an object within the field of view; and

logic that determines a distance or distances to the object within the field of view based on the reflected image.

1. A machine-implemented method, comprising:

transmitting light from a light source in a camera;

raster scanning the light over an object in a field of view of the camera;

receiving one or more reflected images of the light from the object at a detector; and

determining one or more distances to the object based on the one or more reflected images.

2. The machine-implemented method of claim 1, wherein the determining one or more distances to the object based on the one or more reflected images includes determining one or more times-of-flight between transmitting the light from the light source to receiving the one or more reflected images at the detector.

3. The machine-implemented method of claim 2, wherein the transmitting light from a light source includes transmitting a sequence of pulses, the receiving one or more reflected images of the light includes receiving a separate reflected image for each of the pulses, the one or more times-of-flight includes determining a time of flight between transmitting and receiving each of the pulses.

4. The machine-implemented method of claim 1, wherein raster scanning light over an object in the field of view includes raster scanning a pattern in the field of view, the receiving one or more reflected images includes receiving an image of at least a portion of the pattern.

5. The machine-implemented method of claim 4, wherein the determining one or more distances to the object includes analyzing apparent deformations in the at least a portion of the pattern.

6. The machine-implemented method of claim 5, wherein the analyzing apparent deformations in the at least a portion of the pattern that is received includes comparing the at least a portion of the pattern to one or more reference images, each of the one or more reference images is an image that would be received at the detector by raster scanning the pattern over a reference object at a known distance from the camera.

7. The machine-implemented method of claim 1, further comprising:

generating a depth map of the object based on the one or more determined distances to the object.

8. The machine-implemented method of claim 1, further comprising:

dynamically modifying the field of view by varying a range over which the raster scanning is performed.

10. The depth camera of claim 9, wherein the logic determines a distance or distances to the one or more objects within the field of view by determining times-of-flight between transmitting the light source to receiving the reflected image at the light detector.

11. The depth camera of claim 10, wherein the light source transmits a sequence of pulses, the light detector receives a separate reflected image for each of the pulses, the logic determines a time of flight between transmitting and receiving each of the pulses.

12. The depth camera of claim 9, wherein the scanning element scans a pattern of the light from the light source, the light detector is a linear array detector, the distance determination logic determines one or more distances to the object within the field of view by determining spatial differences between a received image of the pattern and a reference image, the reference image is an image that would result by raster scanning the pattern over a reference object at a known distance from the camera.

14. The depth camera of claim 9, further comprising logic that modifies the field of view by varying one or more of scanning in the x-direction or scanning in the y-direction.

12-1. The depth camera of claim 9, wherein the distance determination logic determines a depth map of the object in the field of view.

15. A machine-implemented method of scanning to determine depth information, the method comprising:

transmitting light from a light source in a camera;

controlling a scanning element while transmitting the light to scan a line in a field of view of the camera;

receiving, at a linear array detector in the camera, an image from an object in the field of view, the image corresponds to at least a portion of the line;

determining whether to scan another line;

repeating the transmitting, the controlling, and the receiving if another line is to be scanned;

analyzing spatial properties of the received images; and

determining a distance or distances to the object within the field of view based on the analyzing spatial properties of the received images.

16. The machine-implemented method of claim 15, further comprising generating a 3D mapping of the object in the field of view based on the determined distance or distances.

17. The machine-implemented method of claim 15, wherein the controlling a scanning element includes determining how far to scan the line.

18. The machine-implemented method of claim 17, wherein repeating the transmitting and the controlling scans one or more patterns onto the object, the receiving at the linear array receives data for each of the one or more patterns, the determining how far to scan the line is based on analyzing spatial properties of the one or more received patterns.

19. The machine-implemented method of claim 18, wherein the analyzing spatial properties includes determining spatial differences between the one or more received patterns and a plurality of reference images, the reference images are images that would be received at the linear array detector by raster scanning the one or more patterns over a reference object at known distances.

20. The machine-implemented method of claim 15, wherein the determining a distance or distances to the object within the field of view based on the analyzing spatial properties of the received images includes analyzing apparent deformations in the received images.