US 9,813,616 B2
Feature based high resolution motion estimation from low resolution images captured using an array source
Dan Lelescu, Morgan Hill, CA (US); and Ankit K. Jain, San Diego, CA (US)
Assigned to FotoNation Cayman Limited, San Jose, CA (US)
Filed by FotoNation Cayman Limited, San Jose, CA (US)
Filed on Nov. 5, 2015, as Appl. No. 14/933,871.
Application 14/933,871 is a continuation of application No. 13/975,159, filed on Aug. 23, 2013, abandoned.
Claims priority of provisional application 61/692,547, filed on Aug. 23, 2012.
Prior Publication US 2016/0165134 A1, Jun. 9, 2016
Int. Cl. H04N 5/232 (2006.01); G06T 3/40 (2006.01); H04N 19/53 (2014.01); H04N 19/54 (2014.01); H04N 19/59 (2014.01); G06K 9/46 (2006.01); G06K 9/62 (2006.01); G06T 11/60 (2006.01); G06T 7/13 (2017.01); G06T 7/246 (2017.01)
CPC H04N 5/23232 (2013.01) [G06K 9/4604 (2013.01); G06K 9/6201 (2013.01); G06T 3/4053 (2013.01); G06T 3/4069 (2013.01); G06T 7/13 (2017.01); G06T 7/246 (2017.01); G06T 11/60 (2013.01); H04N 19/53 (2014.11); H04N 19/54 (2014.11); H04N 19/59 (2014.11); G06T 2207/20221 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for performing feature based high resolution motion estimation from a plurality of low resolution images, comprising:
performing feature detection with respect to a first sequence of low resolution images captured by a first imager in an imager array using a processor configured by software to identify initial locations for a plurality of detected features in the first sequence of low resolution images, where the first sequence of low resolution images is part of a set of sequences of low resolution images captured from different perspectives by different imagers in the imager array, a first plurality of images includes one image from each sequence of low resolution images taken by different imagers from different perspectives at a first point in time, and a second plurality of images includes one images from each sequence of low resolution images taken by different imagers from different perspectives at a second point in time;
synthesizing a first set of high resolution image portions from the set of sequences of low resolution images captured from different perspectives using the processor configured by software to perform a super-resolution process using the first plurality of images and parallax information, where the synthesized high resolution image portions contain the identified plurality of detected features from the sequence of low resolution images;
synthesizing a second set of high resolution image portions from the set of sequences of low resolution images captured from different perspectives using the processor configured by software to perform a super-resolution process using the second plurality of images and parallax information, where the synthesized high resolution image portions contain the identified plurality of detected features from the sequence of low resolution images;
performing feature detection within the first and second sets of high resolution image portions to identify locations for said plurality of detected features to a higher precision than the initial locations identified in the low resolution images using the processor configured by software; and
estimating camera motion using the high precision locations for said plurality of detected features using the processor configured by software.