Image rotation from local motion estimates
View Patent ↗A measure of frame-to-frame rotation is determined. Integral projection vector gradients are determined and normalized for a pair of images. Locations of primary maximum and minimum peaks of the integral projection vector gradients are determined. Based on normalized distances between the primary maximum and minimum peaks, a global image rotation is determined.
1. Within an image acquisition device, a method of cross-correlating integral projection vectors, comprising:
acquiring a sequence of image frames;
determining a measure of frame-to-frame rotation, including:
determining horizontal and vertical integral projection vector gradients for each of a first frame and a second, following, image frame in said sequence;
normalizing said integral projection vector gradients;
determining locations of primary maximum and minimum peaks of said integral projection vector gradients, and
based on normalized distances between the primary maximum and minimum peaks, determining a global image rotation; and
performing a further action based on the determined global image rotation.
2. The method of claim 1 , wherein the further action comprises joining adjacent frames of a panorama image; predicting a location of a tracked object in a subsequent frame; providing an image with reduced blur than at least one of the first and second frames; or providing a more stable video sequence by removing one or more undesired motion artifacts, or combinations thereof.
3. The method of claim 1 , further comprising determining horizontal and vertical integral projection vectors for each of the first frame and the second, following, image frame in said sequence; successively convoluting a first integral projection vector with a variable length vector; convoluting a second integral projection vector with a fixed length vector; and determining an absolute sum of differences between filtered vectors based on the convoluting of the first and second integral projection vectors; and wherein the global rotation determining is further based on a length of a variable vector N that leads to a minimum value of the absolute sum of the differences.
4. An image acquisition device, comprising:
a lens, shutter and image sensor for acquiring digital images;
a processor;
a memory having code embedded therein for programming the processor to perform a method of cross-correlating integral projection vectors, wherein the method comprises:
acquiring a sequence of image frames;
determining a measure of frame-to-frame rotation, including:
determining horizontal and vertical integral projection vector gradients for each of a first frame and a second, following, image frame in said sequence;
normalizing said integral projection vector gradients;
determining locations of primary maximum and minimum peaks of said integral projection vector gradients, and
based on normalized distances between the primary maximum and minimum peaks, determining a global image rotation; and
performing a further action based on the determined global image rotation.
5. The device of claim 4 , wherein the further action comprises joining adjacent frames of a panorama image; predicting a location of a tracked object in a subsequent frame; providing an image with reduced blur than at least one of the first and second frames; or providing a more stable video sequence by removing one or more undesired motion artifacts, or combinations thereof.
6. The device of claim 4 , wherein the method further comprises determining horizontal and vertical integral projection vectors for each of the first frame and the second, following, image frame in said sequence; successively convoluting a first integral projection vector with a variable length vector; convoluting a second integral projection vector with a fixed length vector; and determining an absolute sum of differences between filtered vectors based on the convoluting of the first and second integral projection vectors; and wherein the global rotation determining is further based on a length of a variable vector N that leads to a minimum value of the absolute sum of the differences.
7. One or more non-transitory processor-readable media having code embedded therein for programming the processor to perform a method of cross-correlating integral projection vectors, wherein the method comprises:
acquiring a sequence of image frames;
determining a measure of frame-to-frame rotation, including:
determining horizontal and vertical integral projection vector gradients for each of a first frame and a second, following, image frame in said sequence;
normalizing said integral projection vector gradients;
determining locations of primary maximum and minimum peaks of said integral projection vector gradients, and
based on normalized distances between the primary maximum and minimum peaks, determining a global image rotation; and
performing a further action based on the determined global image rotation.
8. The one or more non-transitory processor-readable media of claim 7 , wherein the further action comprises joining adjacent frames of a panorama image; predicting a location of a tracked object in a subsequent frame; providing an image with reduced blur than at least one of the first and second frames; or providing a more stable video sequence by removing one or more undesired motion artifacts, or combinations thereof.
9. The one or more non-transitory processor-readable media of claim 7 , wherein the method further comprises determining horizontal and vertical integral projection vectors for each of the first frame and the second, following, image frame in said sequence; successively convoluting a first integral projection vector with a variable length vector; convoluting a second integral projection vector with a fixed length vector; and determining an absolute sum of differences between filtered vectors based on the convoluting of the first and second integral projection vectors; and wherein the global rotation determining is further based on a length of a variable vector N that leads to a minimum value of the absolute sum of the differences.