US 6,829,384 B2 · Object finder for photographic images

Abstract

An object finder program for detecting presence of a 3D object in a 2D image containing a 2D representation of the 3D object. The object finder uses the wavelet transform of the input 2D image for object detection. A pre-selected number of view-based detectors are trained on sample images prior to performing the detection on an unknown image. These detectors then operate on the given input image and compute a quantized wavelet transform for the entire input image. The object detection then proceeds with sampling of the quantized wavelet coefficients at different image window locations on the input image and efficient look-up of pre-computed log-likelihood tables to determine object presence. The object finder's coarse-to-fine object detection strategy coupled with exhaustive object search across different positions and scales results in an efficient and accurate object detection scheme. The object finder detects a 3D object over a wide range in angular variation (e.g., 180 degrees) through the combination of a small number of detectors each specialized to a small range within this range of angular variation.

Claims37

Dependent claims

A method to detect presence of a 3D (three dimensional) object in a 2D (two dimensional) image containing a 2D representation of said 3D object, said method comprising:

receiving a digitized version of said 2D image;
selecting one or more view-based detectors;
for each view-based detector, computing a wavelet transform of said digitized version of said 2D image, wherein said wavelet transform generates a plurality of transform coefficients, and wherein each transform coefficient represents visual information from said 2D image that is localized in space, frequency, and orientation;
applying said one or more view-based detectors in parallel to respective plurality of transform coefficients, wherein each view-based detector is configured to:
compute a likelihood ratio based on visual information received from corresponding waveform coefficients;
compare said likelihood ratio to a predetermined threshold value;
and
detect a specific orientation of said 3D object in said 2D image based on said comparison of said likelihood ratio to said predetermined threshold value;
combining results of application of said one or more view-based detectors;
and
determining orientation and location of said 3D object from said combination of results of application of said one or more view-based detectors.

8 more elements

A computer-readable storage medium having stored thereon instructions, which, when executed by a processor, cause the processor to perform the following:

digitize a 2D (two dimensional) image, wherein said 2D image contains a 2D representation of a 3D (three dimensional) object;
compute a wavelet transform of said digitized version of said 2D image, wherein said wavelet transform generates a plurality of transform coefficients, and wherein each transform coefficient represents corresponding visual information from said 2D image;
place an image window of fixed size at a first plurality of locations within said 2D image;
evaluate a plurality of visual attributes at each of said first plurality of locations of said image window using corresponding transform coefficients to determine a likelihood ratio corresponding to said each of said first plurality of locations;
and
estimate the presence of said 3D object in said 2D image based on a comparison of said corresponding likelihood ratio to a predetermined threshold value at said each of said first plurality of locations.

3 more elements

A computer system, which, upon being programmed, is configured to perform the following:

receive a digitized version of a 2D (two dimensional) image, wherein said 2D image contains a 2D representation of a 3D (three dimensional) object;
select one or more view-based detectors;
for each view-based detector, compute a wavelet transform of said digitized version of said 2D image, wherein said wavelet transform generates a plurality of transform coefficients, and wherein each transform coefficient represents corresponding visual information from said 2D image;
apply said one or more view-based detectors in parallel to respective plurality of transform coefficients, wherein each view-based detector is configured to:
compute a likelihood ratio based on visual information received from corresponding waveform coefficients;
compare said likelihood ratio to a predetermined threshold value;
and detect a specific orientation of said 3D object in said 2D image based on said comparison of said likelihood ratio to said predetermined threshold value;
combine results of application of said one or more view-based detectors;
and
determine orientation and location of said 3D object from said combination of results of application of said one or more view-based detectors.

7 more elements

A method to detect presence of a 3D (three dimensional) object in a 2D (two dimensional) image containing a 2D representation of said 3D object, said method comprising:

receiving a digitized version of said 2D image;
selecting one or more view-based detectors;
for each view-based detector, computing a wavelet transform of said digitized version of said 2D image, wherein said wavelet transform generates a plurality of transform coefficients, and wherein each transform coefficient represents visual information from said 2D image that is localized in space, frequency, and orientation;
applying said one or more view-based detectors in parallel to respective plurality of transform coefficients, wherein each view-based detector is configured to detect a specific orientation of said 3D object in said 2D image based on visual information received from corresponding transform coefficients;
and wherein applying said one or more view-based detectors in parallel includes the following for at least one of said one or more view-based detectors:
defining a plurality of attributes, wherein each attribute is configured to sample and quantize each of a predetermined number of transform coefficients from said plurality of transform coefficients;
selecting an image window, wherein said image window is configured to represent a fixed size area of said 2D image;
placing said image window at one of a plurality of locations within said 2D image;
selecting two correction factors, wherein each of said two correction factors is configured to correct the light intensity level for a corresponding half of said image window at said one of said plurality of locations;
selecting a predetermined number of correction values for each of said two correction factors;
for each of said two correction factors and for each of said predetermined number of correction values therefor, evaluating the total log-likelihood value for said plurality of attributes for the corresponding half of said image window at said one of said plurality of locations;
for each half of said image window at said one of said plurality of locations, selecting the largest total log-likelihood value for said plurality of attributes;
and
adding corresponding largest total log-likelihood value for said each half of said image window to estimate the presence of said 3D object;
combining results of application of said one or more view-based detectors;
and
determining orientation and location of said 3D object from said combination of results of application of said one or more view-based detectors.

14 more elements

A method to detect presence of a 3D (three dimensional) object in a 2D (two dimensional) image containing a 2D representation of said 3D object, said method comprising:

receiving a digitized version of said 2D image;
selecting one or more view-based detectors;
for each view-based detector, computing a wavelet transform of said digitized version of said 2D image, wherein said wavelet transform generates a plurality of transform coefficients, and wherein each transform coefficient represents visual information from said 2D image that is localized in space, frequency, and orientation;
applying said one or more view-based detectors in parallel to respective plurality of transform coefficients, wherein each view-based detector is configured to detect a specific orientation of said 3D object in said 2D image based on visual information received from corresponding transform coefficients;
and wherein applying said one or more view-based detectors in parallel includes the following for at least one of said one or more view-based detectors:
defining a plurality of attributes, wherein each attribute is configured to sample and quantize each of a predetermined number of transform coefficients from said plurality of transform coefficients;
selecting an image window, wherein said image window is configured to represent a fixed size area of said 2D image;
placing said image window at a first one of a first plurality of locations within said 2D image;
for each of said plurality of attributes, determining a corresponding attribute value at each of a first plurality of coordinates within said image window at said first location;
for each of said plurality of attributes, obtaining a first class-conditional probability for an object class and a second class-conditional probability for a non-object class at said each of said first plurality of coordinates based on said corresponding attribute values determined at said first plurality of coordinates;
estimating presence of the 3D object in said image window at said first location based on a ratio of a first product and a second product, wherein said first product includes a product of all of said first class-conditional probabilities and wherein said second product includes a product of all of said second class-conditional probabilities;
moving said image window to a second one of said first plurality of locations within said 2D image;
and
continuing determination of said corresponding attribute values and said first and said second class-conditional probabilities, and estimation of the presence of said 3D object in said image window at said second location and at each remaining location in said first plurality of locations within said 2D image;
combining results of application of said one or more view-based detectors;
and
determining orientation and location of said 3D object from said combination of results of application of said one or more view-based detectors.

14 more elements

A method to detect presence of a 3D (three dimensional) object in a 2D (two dimensional) image containing a 2D representation of said 3D object, said method comprising:

receiving a digitized version of said 2D image;
selecting one or more view-based detectors;
for each view-based detector, computing a wavelet transform of said digitized version of said 2D image, wherein said wavelet transform generates a plurality of transform coefficients, and wherein each transform coefficient represents visual information from said 2D image that is localized in space, frequency, and orientation;
applying said one or more view-based detectors in parallel to respective plurality of transform coefficients, wherein each view-based detector is configured to detect a specific orientation of said 3D object in said 2D image based on visual information received from corresponding transform coefficients;
and wherein applying said one or more view-based detectors in parallel includes the following for at least one of said one or more view-based detectors:
defining a plurality of attributes, wherein each attribute is configured to sample and quantize each of a predetermined number of transform coefficients from said plurality of transform coefficients;
selecting an image window, wherein said image window is configured to represent a fixed size area of said 2D image;
placing said image window at a plurality of locations within said 2D image;
for each attribute in a subset of said plurality of attributes, determining a corresponding attribute value at each of a plurality of coordinates within said image window at each of said plurality of locations;
for each attribute in said subset of said plurality of attributes, obtaining a first class-conditional probability for an object class and a second class-conditional probability for a non-object class at said each of said plurality of coordinates at said each of said plurality of locations based on said corresponding attribute values determined at said plurality of coordinates;
computing a plurality of ratios, wherein each ratio corresponds to a different one of said plurality of locations of said image window, wherein said each ratio is a division of a first product and a second product, and wherein said first product includes a product of all of said first class-conditional probabilities and wherein said second product includes a product of all of said second class-conditional probabilities at corresponding one of said plurality of locations of said image window;
determining which of said plurality of ratios are above a predetermined threshold value;
and
estimating presence of said 3D object at only those of said plurality of locations where corresponding ratios are above said predetermined threshold value;
combining results of application of said one or more view-based detectors;
and
determining orientation and location of said 3D object from said combination of results of application of said one or more view-based detectors.

14 more elements

A method to detect presence of a 3D (three dimensional) object in a 2D (two dimensional) image containing a 2D representation of said 3D object, said method comprising:

receiving a digitized version of said 2D image;
selecting one or more view-based detectors;
for each view-based detector, computing a wavelet transform of said digitized version of said 2D image, wherein said wavelet transform generates a plurality of transform coefficients, and wherein each transform coefficient represents visual information from said 2D image that is localized in space, frequency, and orientation;
applying said one or more view-based detectors in parallel to respective plurality of transform coefficients, wherein each view-based detector is configured to detect a specific orientation of said 3D object in said 2D image based on visual information received from corresponding transform coefficients;
and wherein applying said one or more view-based detectors in parallel includes the following for at least one of said one or more view-based detectors:
defining a plurality of attributes, wherein each attribute is configured to sample and quantize each of a predetermined number of transform coefficients from said plurality of transform coefficients;
for each of said plurality of attributes, determining a corresponding attribute value at each of a plurality of coordinate locations within said 2D image;
selecting an image window, wherein said image window is configured to represent a fixed size area of said 2D image;
placing said image window at a first one of a plurality of locations within said 2D image;
for each of said plurality of attributes, selecting those corresponding attribute values that fall within said first location of said image window;
for each of said plurality of attributes, obtaining a first class-conditional probability for an object class and a second class-conditional probability for a non-object class based on said selected attribute values that fall within said first location of said image window;
estimating presence of the 3D object in said image window at said first location based on a ratio of a first product and a second product, wherein said first product includes a product of all of said first class-conditional probabilities and wherein said second product includes a product of all of said second class-conditional probabilities;
moving said image window to a second one of said plurality of locations within said 2D image;
and
continuing selection of corresponding attribute values, determination of said first and said second class-conditional probabilities, and estimation of the presence of said 3D object in said image window at said second location and at each remaining location in said plurality of locations within said 2D image;
combining results of application of said one or more view-based detectors;
and
determining orientation and location of said 3D object from said combination of results of application of said one or more view-based detectors.

15 more elements

A computer system, which, upon being programmed, is configured to perform the following:

receive a digitized version of a 2D (two dimensional) image, wherein said 2D image contains a 2D representation of a 3D (three dimensional) object;
select one or more view-based detectors;
for each view-based detector:
compute a wavelet transform of said digitized version of said 2D image, wherein said wavelet transform generates a plurality of transform coefficients, and wherein each transform coefficient represents corresponding visual information from said 2D image;
select a plurality of attributes, wherein each attribute is configured to
sample and quantize each of a predetermined number of transform coefficients from said plurality of transform coefficients;
place an image window at a first one of a plurality of locations within said 2D image, wherein said image window is configured to represent a fixed size area of said 2D image;
for each of said plurality of attributes, determine a corresponding attribute value at each of a plurality of coordinates within said image window at said first location;
for each of said plurality of attributes, compute a first class-conditional probability for an object class and a second class-conditional probability for a non-object class at said each of said plurality of coordinates based on said corresponding attribute values determined at said plurality of coordinates;
estimate the presence of the 3D object in said image window at said first location based on a ratio of a first product and a second product, wherein said first product includes a product of all of said first class-conditional probabilities and wherein said second product includes a product of all of said second class-conditional probabilities;
move said image window to a second one of said plurality of locations within said 2D image;
and
continue determination of said corresponding attribute values and said first and said second class-conditional probabilities, and estimation of the presence of said 3D object in said image window at said second location and at each remaining location in said plurality of locations within said 2D image;
apply said one or more view-based detectors in parallel to respective plurality of transform coefficients, wherein each view-based detector is configured to detect a specific orientation of said 3D object in said 2D image based on visual information received from corresponding transform coefficients;
combine results of application of said one or more view-based detectors;
and
determine orientation and location of said 3D object from said combination of results of application of said one or more view-based detectors.

14 more elements

Dependencies are inferred from the claim text.

Object finder for photographic images

Life of this patent

Object finder for photographic images

Life of this patent

Abstract

Claims37