Gaze correction of multi-view images

• US 10,321,123 B2
• Filed: 01/04/2017
• Issued: 06/11/2019
• Est. Priority Date: 01/05/2016
• Status: Active Grant

• Current Assignee: Reald Spark, LLC
• Original Assignee: Reald Spark, LLC
• Inventors: Sommerlade, Eric, Robinson, Michael G.
• Primary Examiner(s): Philippe, Gims S
• Application Number:
  US15/397,951
• Publication Number:
  US 20170195662A1
• Time in Patent Office: 888 Days
• Field of Search: 348 1416, 382154
• CPC Class Codes: G06F 3/011 Arrangements for interaction with the human body, e.g. for user immersion in virtual reality blind teaching G09B21/00
• CPC Class Codes: G06F 3/013 Eye tracking input arrangements G06F3/015 takes precedence
• CPC Class Codes: G06V 10/462 Salient features, e.g. scale invariant feature transforms [SIFT]
• CPC Class Codes: G06V 10/62 relating to a temporal dimension, e.g. time-based feature extraction; Pattern tracking
• CPC Class Codes: G06V 40/193 Preprocessing; Feature extraction
• CPC Class Codes: H04N 13/117 the virtual viewpoint locations being selected by the viewers or determined by viewer tracking
• CPC Class Codes: H04N 13/344 with head-mounted left-right displays
• CPC Class Codes: H04N 7/147 Communication arrangements, e.g. identifying the communication as a video-communication, intermediate storage of the signals selecting H04Q
• CPC Class Codes: H04N 7/15 Conference systems

Abstract

Gaze is corrected by adjusting multi-view images of a head. Image patches containing the left and right eyes of the head are identified and a feature vector is derived from plural local image descriptors of the image patch in at least one image of the multi-view images. A displacement vector field representing a transformation of an image patch is derived, using the derived feature vector to look up reference data comprising reference displacement vector fields associated with possible values of the feature vector produced by machine learning. The multi-view images are adjusted by transforming the image patches containing the left and right eyes of the head in accordance with the derived displacement vector field.

Claims

1. A device for adjusting multi-view images of a head to correct gaze, the device comprising an image processor arranged to process the multi-view images of a head by:

in each image, identifying image patches containing the left and right eyes of the head, respectively;

in respect of the image patches containing the left eyes of the head in each image of the multi-view images, and also in respect of the image patches containing the right eyes of the head in each image of the multi-view images, performing the steps of;

deriving a feature vector from plural local image descriptors of the image patch in at least one image of the multi-view images; and

deriving a displacement vector field representing a transformation of an image patch, using the derived feature vector to look up reference data comprising reference displacement vector fields associated with possible values of the feature vector; and

adjusting each image of the multi-view images by transforming the image patches containing the left and right eyes of the head in accordance with the derived displacement vector field.

2. A device according to claim 1, further comprising a camera system arranged to capture the multi-view images.

3. A device according to claim 1, further comprising a telecommunications interface arranged to transmit the adjusted images over a telecommunications network to a destination device for display thereon.

4. A device according to claim 1, wherein the multi-view images are a stereoscopic pair of images.

5. A device according to claim 4, wherein said plural local image descriptors are plural local image descriptors in both images of the stereoscopic pair;

and

wherein the image processor is further arranged to process the multi-view images such that the deriving of the displacement vector fields further comprises;

deriving an initial displacement vector field representing a notional transformation of a notional image patch in a notional image having a notional camera location relative to the camera locations of the multi-view images, using the derived feature vector to look up reference data comprising reference displacement vector fields associated with possible values of the feature vector; and

deriving displacement vector fields representing a transformation of the image patches in each image of the multi-view images by transforming the initial displacement vector field in accordance with an estimate of the optical flows between the notional image patches in the notional images and the image patches in the images of the multi-view images.

6. A device according to claim 5, wherein the notional camera location is between the camera locations of the images of the stereoscopic pair.

7. A device according to claim 1, wherein

said plural local image descriptors are plural local image descriptors in each images of the multi-view images, and

said reference data comprising pairs of reference displacement vector fields for each image of the multi-view images, which pairs of reference displacement vector fields are associated with possible values of the feature vector.

8. A device according to claim 1, wherein said plural local image descriptors are plural local image descriptors in one image of the multi-view images;

and

wherein the image processor is further arranged to process the multi-view images such that the deriving of the displacement vector fields further comprises;

deriving a displacement vector field representing a transformation of the image patch in said one image of the multi-view images, using the derived feature vector to look up reference data comprising reference displacement vector fields associated with possible values of the feature vector; and

deriving a displacement vector field representing a transformation of the image patch in the other multi-view image or images by transforming the derived displacement vector field representing a transformation of the image patch in said one image of the multi-view images in accordance with an estimate of the optical flow between the image patches in said one image of the multi-view images and the other multi-view image or images.

9. A device according to claim 1, wherein the image processor is further arranged to process the multi-view images such that:

the deriving of the displacement vector fields further comprises deriving displacement vector fields in respect of the image patches in each image of the multi-view images, and

the transforming of the image patches containing the left and right eyes of the head is performed in accordance with the displacement vector fields derived in respect of the image patches in each image of the multi-view images.

10. A device according to claim 1, wherein the image processor is further arranged to process the multi-view images such that:

the deriving of the displacement vector field further comprises deriving displacement vector fields in respect of the image patches in each image of the multi-view images, and further deriving a merged displacement vector field from the displacement vector fields derived in respect of the image patches in each image of the multi-view images, and

the transforming of the image patches containing the left and right eyes of the head is performed in accordance with the merged displacement vector field.

11. A device according to claim 10, wherein the reference displacement vector fields are further associated with confidence values;

wherein the image processor is further arranged to process the multi-view images such that the deriving of the displacement vector fields further comprises;

deriving a confidence value associated with each derived displacement vector field, and

deriving the merged displacement vector field as an average of the displacement vector fields derived in respect of the image patches in each image of the multi-view images weighted by the derived confidence values.

12. A device according to claim 1, wherein the image processor is further arranged to process the multi-view using location data representing an observer location relative to a display location of the multi-view images;

wherein said reference data comprises plural sets of reference displacement vector fields associated with possible values of the feature vector, which sets are associated with different observer locations; and

wherein the image processor is further arranged to process the multi-view images such that the deriving of the displacement vector fields further comprises using the derived feature vector to look up the set of reference displacement vector fields associated with the observer location represented by the location data.

13. A device according to claim 1, wherein the local image descriptors comprise local image descriptors derived in a normalized coordinate system, and the reference and derived displacement vector fields are displacement vector fields in the same normalized coordinate system.

14. A device according to claim 1, wherein

the feature vector comprises features that are values derived from the local image descriptors in a discrete space,

the reference displacement vector fields comprise a reference displacement vector field associated with each possible value of the feature vector in the discrete space, and

the image processor is further arranged to process the multi-view images such that the deriving of the displacement vector fields further comprises selecting the reference displacement field associated with the actual value of the derived feature vector.

15. A device according to claim 1, wherein

the feature vector comprises features that are discrete values of the local image descriptors in a continuous space, and

the image processor is further arranged to process the multi-view images such that the deriving of the displacement vector fields further comprises interpolating a displacement vector field from the reference displacement vector fields based on the relationship between the actual value of the derived feature vector and the values of the feature vector associated with the reference displacement vector fields.