Method for automatic detection of human eyes in digital images
AssigneeEastman Kodak Company
InventorJiebo Luo
Life of this patent
Estimating the term…
Abstract
A computer program product for locating first and second objects, each having substantially the same physical characteristics, and the ratio of the distance between the first and second objects and the size of each object is substantially invariant, the computer program product comprises: a computer readable storage medium having a computer program stored thereon for performing the steps of determining potential flesh regions in an image; determining valley regions in an image; performing template matching for determining a plurality of locations that give a desirable match of the object relative to the template; and performing verification for determining the likelihood of pairs of potential eye candidates at the locations determined in the performing template matching step.
Claims49
A computer program product for locating first and second human eye objects each having substantially the same physical characteristics, and the ratio of the distance between the first and second human eye objects and the size of each human eye object is substantially invariant, the computer program product comprising:
- a computer readable storage medium having a computer program stored thereon for performing the steps of:
- (a) determining a potential flesh region in an intensity image;
- (b) determining valley regions in the intensity image for determining substantially non-flat regions with lower intensity values in a local area of the intensity image;
- (c) performing matching in the intensity image using an intensity-based template in a neighborhood of the valley regions within the flesh regions for determining a plurality of locations that give a desirable match of the human eye object relative to the template, said step of matching using cross-correlation to identify desirable locations;
- and
- (d) performing verification by mating a pair of potential human eye object candidates with desirable matching response to the template by using a plurality of verification criteria selected from the group including the orientation, proportion, profile, symmetry, and centrality of the paired human eye objects matched to the intensity-based template, wherein the verification criteria comprise finding the best pair of locations of human eye objects by computing figures of merit individually or in combination for the plurality of verification criteria, and wherein the figure of merit for orientation includes measuring the difference between an orientation of a line connecting the first and second human eye objects, and an average orientation of the first and second human eye objects.
A computer program product for locating first and second human eye objects each having substantially the same physical characteristics, and the ratio of the distance between the first and second human eye objects and the size of each human eye object is substantially invariant, the computer program product comprising:
- a computer readable storage medium having a computer program stored thereon for performing the steps of:
- (a) determining a potential flesh region in an intensity image;
- (b) determining valley regions in the intensity image for determining substantially non-flat regions with lower intensity values in a local area of the intensity image;
- (c) performing matching in the intensity image using an intensity-based template in a neighborhood of the valley regions within the flesh regions for determining a plurality of locations that give a desirable match of the human eye object relative to the template, said step of matching using cross-correlation to identify desirable locations;
- and
- (d) performing verification by mating a pair of potential human eye object candidates with desirable matching response to the template by using a plurality of verification criteria selected from the group including the orientation, proportion, profile, symmetry, and centrality of the paired human eye objects matched to the intensity-based template, wherein the verification criteria comprise finding the best pair of locations of human eye objects by computing figures of merit individually or in combination for the plurality of verification criteria, and wherein the figure of merit for symmetry includes computing the symmetry between first and second halves of a face window determined by the locations of the human eye objects.
A computer program product for locating first and second human eye objects each having substantially the same physical characteristics, and the ratio of the distance between the first and second human eye objects and the size of each human eye object is substantially invariant, the computer program product comprising:
- a computer readable storage medium having a computer program stored thereon for performing the steps of:
- (a) determining a potential flesh region in an intensity image;
- (b) determining valley regions in the intensity image for determining substantially non-flat regions with lower intensity values in a local area of the intensity image;
- (c) performing matching in the intensity image using an intensity-based template in a neighborhood of the valley regions within the flesh regions for determining a plurality of locations that give a desirable match of the human eye object relative to the template, said step of matching using cross-correlation to identify desirable locations;
- and
- (d) performing verification by mating a pair of potential human eye object candidates with desirable matching response to the template by using a plurality of verification criteria selected from the group including the orientation, proportion, profile, symmetry, and centrality of the paired human eye objects matched to the intensity-based template, wherein the verification criteria comprise finding the best pair of locations of human eye objects by computing figures of merit individually or in combination for the plurality of verification criteria, and wherein the figure of merit for centrality includes computing a distance from a middle point between the first and second human eye objects to a major axis of the determined flesh region.
A method for locating first and second human eye objects each having substantially the same physical characteristics, and the ratio of the distance between the first and second human eye objects and the size of each human eye object is substantially invariant, said method comprising the steps of:
- (a) determining a potential flesh region in an intensity image;
- (b) determining valley regions in the intensity image for determining substantially non-flat regions with lower intensity values in a local area of the intensity image;
- (c) performing matching in the intensity image using an intensity-based template in a neighborhood of the valley regions within the flesh regions for determining a plurality of locations that give a desirable match of the human eye object relative to the template, said step of matching using cross-correlation to identify desirable locations;
- and
- (d) performing verification by mating a pair of potential human eye object candidates with desirable matching response to the template by using a plurality of verification criteria selected from the group including the orientation, proportion, profile, symmetry, and centrality of the paired human eye objects matched to the intensity-based template, wherein the verification criteria comprise finding the best pair of locations of human eye objects by computing figures of merit individually or in combination for the plurality of verification criteria, and wherein the figure of merit for orientation includes measuring the difference between an orientation of a line connecting the first and second human eye objects, and an average orientation of the first and second human eye objects.
A method for locating first and second human eye objects each having substantially the same physical characteristics, and the ratio of the distance between the first and second human eye objects and the size of each human eye object is substantially invariant, said method comprising the steps of:
- (a) determining a potential flesh region in an intensity image;
- (b) determining valley regions in the intensity image for determining substantially non-flat regions with lower intensity values in a local area of the intensity image;
- (c) performing matching in the intensity image using an intensity-based template in a neighborhood of the valley regions within the flesh regions for determining a plurality of locations that give a desirable match of the human eye object relative to the template, said step of matching using cross-correlation to identify desirable locations;
- and
- (d) performing verification by mating a pair of potential human eye object candidates with desirable matching response to the template by using a plurality of verification criteria selected from the group including the orientation, proportion, profile, symmetry, and centrality of the paired human eye objects matched to the intensity-based template, wherein the verification criteria comprise finding the best pair of locations of human eye objects by computing figures of merit individually or in combination for the plurality of verification criteria, and wherein the figure of merit symmetry includes computing the symmetry between first and second halves of a face window determined by the locations of the human eye objects.
A method for locating first and second human eye objects each having substantially the same physical characteristics, and the ration of the distance between the first and second human eye objects and the size of each human eye object is substantially invariant, said method comprising the steps of:
- (a) determining a potential flesh regions in an intensity image;
- (b) determining valley regions in the intensity image for determining substantially non-flat regions with lower intensity values in a local area of the intensity image;
- (c) performing matching in the intensity image using an intensity-based template in a neighborhood of the valley regions within the flesh regions for determining a plurality of locations that give a desirable match of the human eye object relative to the template, said step of matching using cross-correlation to identify desirable locations;
- and
- (d) performing verification by mating a pair of potential human eye object candidates with desirable matching response to the template by using a plurality of verification criteria selected from the group including the orientation, proportion, profile, symmetry, and centrality of the paired human eye objects matched to the intensity-based template, wherein the verification criteria comprise finding the best pair of locations of human eye objects by computing figures of merit individually or in combination for the plurality of verification criteria, and wherein the figure of merit centrality includes computing a distance from a middle point between the first and second human objects to a major axis of the determined flesh region.
Dependencies are inferred from the claim text.