WO2010018880A1 - Apparatus and method for depth estimation from single image in real time - Google Patents
Apparatus and method for depth estimation from single image in real time Download PDFInfo
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- G06T7/529—Depth or shape recovery from texture
Definitions
- the present invention relates to an apparatus and a method for estimating depths for pixels from a single two-dimensional image.
- Camera lenses for obtaining an image with shallow depth of field are in use to estimate depths for respective pixels from a two-dimensional image. Upon use of such an image, focused portions of the image are clear, and the remaining portions thereof are blurred. Moreover, as a target object becomes far away from a focused object, an image of the target object becomes more blurred. Then, upon focusing on an object closest to a camera lens, how far away target objects are from the closest object in terms of image depth may be estimated by measuring a blur degree from the images of the target objects. As a result, the depth from the center of a camera lens to a target object may be recognized for each pixel by adding the distance between a focused object and the camera lens to the distance value estimated using the blur degree of an image of the target object.
- Documents 1 to 3 as follows. In Documents 1 to 3, depths for respective pixels are estimated from a single image with a shallow depth of field.
- a method for estimating depths for pixels in a single two-dimensional image which includes: creating local deviation images by applying different sizes of windows to the two- dimensional image; creating equalized images by applying windows of different sizes to the respective local deviation images and equalizing portions of the respective local deviation images that have different intensities; and creating a depth map using the equalized deviation images.
- a depth estimation apparatus which includes: a local deviation image creation unit for creating local deviation images by applying windows of different sizes to a single two- dimensional image applied thereto; an intensity equalization unit for creating equalized deviation images by applying windows of different sizes to the local deviation images and equalizing portions of the local deviation images that have different intensities; and a depth map creation unit for creating a depth map using the equalized deviation images.
- real-time depth estimation is possible by carrying out operations according to different sizes of windows in the process of estimating depths for respective pixels from a single two-dimensional image. Furthermore, no separate camera for production of a stereo image is necessary, and a real-time depth estimation may be easily employed in a general camera.
- FIG. 1 is a block diagram schematically illustrating an apparatus for estimating depths for pixels in an image in accordance with an embodiment of the present invention.
- FIG. 2 is a detailed block diagram illustrating the depth estimation apparatus illustrated in Fig. 1. Best Mode for Carrying Out the Invention
- the basic principle of depth estimation in the present invention is that deviations of pixel values are measured according to different sizes of the windows and then are compared with each other in the same image coordinates.
- a target object in the corresponding image coordinate is considered to be close to a focused object.
- a target object at the corresponding image coordinate is considered to be far away from a focused object.
- the depth estimation apparatus of the present invention includes a local deviation image creation unit 12, an intensity equalization unit 14, and a depth map creation unit 16.
- the local deviation image creation unit 12 obtains local deviation images according to different sizes of windows using a single two-dimensional image provided thereto.
- the intensity equalization unit 14 equalizes the width with a large intensity in the respective deviation images provided from the local deviation image creation unit 12 to produce equalized deviation images.
- the depth map creation unit 16 creates a depth map for determining depth values for respective pixels using the equalized images obtained by the intensity equalization unit.
- All the components of the depth estimation apparatus of the present invention such as the local deviation image creation unit 12, an intensity equalization unit 14, and a depth map creation unit 16, and all the processes carried out by the components may be realized by hardware in which a three-stage pipeline structure may be employed for parallel processing.
- a single depth map is produced thereform.
- the size of the depth image produced from the depth estimation apparatus is the same as that of the single two-dimensional image, and the pixel values in the depth map reflect how far a target object including the pixels is spaced apart from a focused object. If the pixel values are small in the depth map, it means that the target object is near to the focused object. On the contrary, if the pixel values are large in the depth map, it means that the target object is far away from the focused object.
- the pixel values in the depth map are discontinuous and finite. Assuming the set of the pixel values is 'A', the number of elements in the set 'A' can be adjusted, and is defined as the depth resolution of 'A' and is indicated as 'R'.
- FIG. 2 shows a detailed block diagram of the depth estimation apparatus illustrated in
- the deviation image creation unit 12 includes R- number of local deviation calculators 21, 23, ..., and 25.
- the local deviation calculators 21, 23, ..., and 25 have different sizes of windows 22, 24, ..., and 26 allocated thereto and create local deviation images according to the sizes of windows from a single two-dimensional image, respectively.
- the term 'local' indicates that a local deviation image is created not by obtaining the deviation on the intensities of the entire pixels in the two-dimensional image but by obtaining the deviation for pixels in a window applied to the two-dimensional image. The obtained deviation is applied to the respective pixels in the two-dimensional image, thereby producing a local deviation image.
- the following rules are used to determine the sizes of windows used in the respective local deviation calculators. More particularly, the windows are sequentially allocated to the local deviation calculators from the one of the smallest size to the one of the largest size, respectively.
- the size of a window for obtaining a local deviation image of i-th index is (i+2) by (i+2).
- the range of the indices is ⁇ 0, 1, 2, -, (R-3), (R-2), and (R-l) ⁇ .
- the local deviation images created by the local deviation image creating unit 12 are provided to the intensity equalization unit 14.
- the intensity equalization unit 14 includes the same number of maximum filters 31,
- the maximum filters 31, 33, ... and 35 have different sizes of windows 32, 34, ..., and 36 allocated thereto and equalize the widths with high intensities in the deviation images provided from the corresponding local deviation calculators 21, 23, ..., and 25, respectively.
- the maximum filters 31, 33, ..., 35 are used to equalize the widths of the portions with high intensities in the local deviation images, respectively.
- the maximum filters select the maximum values of the pixels in the windows applied to the local deviation images, so that portions with high intensities in the local deviation images are made thicker.
- the degree by which a portion with a high intensity in a local deviation image makes thicker in width thereof can be adjusted by making the sizes of windows different from each other.
- the size of a window used in a maximum filter is small, the degree by which a portion with a high intensity in a local deviation image becomes thicker is very small.
- the size of a window used in a maximum filter is large, the degree by which a portion with a high intensity in a local deviation image becomes thicker is increased.
- a rule is applied when the sizes of windows used in maximum filters are determined.
- the windows are sequentially applied from the one of the largest size to the one of the smallest size opposite to the sequence of allocation of the sizes of windows by the deviation calculators.
- the window size having an i-th index for obtaining an equalized deviation image from a maximum filter is (R-i) by (R-i).
- the range of the indices is ⁇ 0, 1, 2, •••, (R-3), (R-2), and (R-l) ⁇ .
- the local deviation image to which a 2 by 2 window is applied is equalized by a maximum filter having the window size of 10 by 10. Accordingly, the equalized images are obtained by applying local deviations and maximum filtering in a single two-dimensional image.
- the equalized deviation images created by the maximum filters are provided to the depth map creating unit 16.
- the depth map creating unit 16 creates a depth map by using the equalized deviation images provided from the intensity equalization unit 14.
- the intensities of pixels represent absolute distances between points on an object and a focal plane, respectively.
- the depth map is obtained by comparing the intensities of pixels in the equalized deviation images at the same image coordinates.
- the depth map creation unit 16 compares the intensities of the pixels, selects a largest pixel among them and determines which index the largest pixel is located at.
- the embodiment of the present invention employs a belief propagation algorithm in the depth map creation unit 16 to solve the above-mentioned disadvantages.
- the belief propagation algorithm enables acquisition of a depth map by using a plurality of equalized images obtained by the filter module 14.
- a process to obtain a depth map in the depth map creation unit 16 is the same that of described above, that is, the depth map is also obtained by comparing intensities of equalized images in the same image coordinates.
- the belief propagation algorithm allows adjacent pixels to have similar depth map values to thereby obtain a more accurate depth map.
- depths for respective pixels can be estimated from a single two-dimensional image, and depth information can be obtained by processing depth estimating operations in parallel.
Abstract
A method for estimating depths for pixels in a single two-dimensional image includes creating local deviation images by applying different sizes of windows to the two-dimensional image, creating equalized images by applying windows of different sizes to the respective local deviation images and equalizing portions of the respective local deviation images that have different intensities. And then, a depth map is created using the equalized deviation images.
Description
Description
APPARATUS AND METHOD FOR DEPTH ESTIMATION FROM SINGLE IMAGE IN REAL TIME
Technical Field
[1] The present invention relates to an apparatus and a method for estimating depths for pixels from a single two-dimensional image.
[2]
Background Art
[3] Camera lenses for obtaining an image with shallow depth of field are in use to estimate depths for respective pixels from a two-dimensional image. Upon use of such an image, focused portions of the image are clear, and the remaining portions thereof are blurred. Moreover, as a target object becomes far away from a focused object, an image of the target object becomes more blurred. Then, upon focusing on an object closest to a camera lens, how far away target objects are from the closest object in terms of image depth may be estimated by measuring a blur degree from the images of the target objects. As a result, the depth from the center of a camera lens to a target object may be recognized for each pixel by adding the distance between a focused object and the camera lens to the distance value estimated using the blur degree of an image of the target object.
[4] Conventional methods for estimating depths using a single image are disclosed in
Documents 1 to 3 as follows. In Documents 1 to 3, depths for respective pixels are estimated from a single image with a shallow depth of field.
[5] [Document 1] Anat Levin, Rob Fergus, Fredo Durand, and William T. Freeman.
Image and Depth from a Conventional camera with a Coded Aperture. ACM Transactions on Graphics, 26(3), July 2007.
[6] [Document 2] Jaeseung Ko, Manbae Kim, and Changick Kim. 2Dd-to-3D
Stereoscopic Conversion: Depth-Map Estimation in a 2D Single- View Image. In Proceedings of SPIE Applications of Digital Image Processing XXIX, August 2007.
[7] [Document 3] Soonmin Bae and Fredo Durand. Defocus Magnification. Computer
Graphics Forum, 26(3):571579, September 2007.
[8] In Documents 1 to 3 for estimating depths corresponding to respective pixels in a single image, the depths cannot be estimated in real time. In other words, more than 33ms is consumed using a personal computer to calculate the depth of several hundreds of thousands of pixels contained in the single image. For this reason, the conventional methods cannot be used in the field of intelligent robotics that requires real time processing. The reason why is that a set of complex operations are processed in
series in the method of the above-mentioned documents.
[9] Accordingly, a method and an apparatus for processing a simple operation performed to estimate depths corresponding to respective pixels in a single two-dimensional image in real time are inevitably necessary. Disclosure of Invention Technical Problem
[10] Therefore, it is an object of the present invention is to provide a method and an apparatus for estimating depths corresponding to respective pixels in a single two- dimensional image.
[H]
Technical Solution
[12] In accordance with an aspect of the present invention, there is provided a method for estimating depths for pixels in a single two-dimensional image, which includes: creating local deviation images by applying different sizes of windows to the two- dimensional image; creating equalized images by applying windows of different sizes to the respective local deviation images and equalizing portions of the respective local deviation images that have different intensities; and creating a depth map using the equalized deviation images.
[13] In accordance with an aspect of the present invention, there is provided a depth estimation apparatus, which includes: a local deviation image creation unit for creating local deviation images by applying windows of different sizes to a single two- dimensional image applied thereto; an intensity equalization unit for creating equalized deviation images by applying windows of different sizes to the local deviation images and equalizing portions of the local deviation images that have different intensities; and a depth map creation unit for creating a depth map using the equalized deviation images.
[14]
Advantageous Effects
[15] According to the present invention, real-time depth estimation is possible by carrying out operations according to different sizes of windows in the process of estimating depths for respective pixels from a single two-dimensional image. Furthermore, no separate camera for production of a stereo image is necessary, and a real-time depth estimation may be easily employed in a general camera.
[16]
Brief Description of the Drawings
[17] The above and other objects and features of the present invention will become apparent from the following description of embodiments given in conjunction with the
accompanying drawings, in which:
[18] Fig. 1 is a block diagram schematically illustrating an apparatus for estimating depths for pixels in an image in accordance with an embodiment of the present invention; and
[19] Fig. 2 is a detailed block diagram illustrating the depth estimation apparatus illustrated in Fig. 1. Best Mode for Carrying Out the Invention
[20] Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings.
[21] The basic principle of depth estimation in the present invention is that deviations of pixel values are measured according to different sizes of the windows and then are compared with each other in the same image coordinates. When the deviation value for pixels in an image of a small window size are greater than that of pixels in an image of a different window size, a target object in the corresponding image coordinate is considered to be close to a focused object. On the other hand, when the deviation value for pixels in an image of a large window size is greater than that of pixels in an image of a different window size, a target object at the corresponding image coordinate is considered to be far away from a focused object.
[22] Referring now to Fig. 1, there is shown a block diagram of a depth estimation apparatus using a single two-dimensional image in accordance with an embodiment of the present invention. The depth estimation apparatus of the present invention includes a local deviation image creation unit 12, an intensity equalization unit 14, and a depth map creation unit 16.
[23] The local deviation image creation unit 12 obtains local deviation images according to different sizes of windows using a single two-dimensional image provided thereto.
[24] The intensity equalization unit 14 equalizes the width with a large intensity in the respective deviation images provided from the local deviation image creation unit 12 to produce equalized deviation images.
[25] The depth map creation unit 16 creates a depth map for determining depth values for respective pixels using the equalized images obtained by the intensity equalization unit.
[26] All the components of the depth estimation apparatus of the present invention, such as the local deviation image creation unit 12, an intensity equalization unit 14, and a depth map creation unit 16, and all the processes carried out by the components may be realized by hardware in which a three-stage pipeline structure may be employed for parallel processing.
[27] In the embodiment of the present invention, when a single two-dimensional image is employed in the depth estimation apparatus, a single depth map is produced thereform.
In this case, the size of the depth image produced from the depth estimation apparatus is the same as that of the single two-dimensional image, and the pixel values in the depth map reflect how far a target object including the pixels is spaced apart from a focused object. If the pixel values are small in the depth map, it means that the target object is near to the focused object. On the contrary, if the pixel values are large in the depth map, it means that the target object is far away from the focused object. In this regard, the pixel values in the depth map are discontinuous and finite. Assuming the set of the pixel values is 'A', the number of elements in the set 'A' can be adjusted, and is defined as the depth resolution of 'A' and is indicated as 'R'.
[28] Fig. 2 shows a detailed block diagram of the depth estimation apparatus illustrated in
Fig. 1.
[29] The deviation image creation unit 12 includes R- number of local deviation calculators 21, 23, ..., and 25. The local deviation calculators 21, 23, ..., and 25 have different sizes of windows 22, 24, ..., and 26 allocated thereto and create local deviation images according to the sizes of windows from a single two-dimensional image, respectively. In this connection, the term 'local' indicates that a local deviation image is created not by obtaining the deviation on the intensities of the entire pixels in the two-dimensional image but by obtaining the deviation for pixels in a window applied to the two-dimensional image. The obtained deviation is applied to the respective pixels in the two-dimensional image, thereby producing a local deviation image.
[30] According to the embodiment of the present invention, the following rules are used to determine the sizes of windows used in the respective local deviation calculators. More particularly, the windows are sequentially allocated to the local deviation calculators from the one of the smallest size to the one of the largest size, respectively. For example, the size of a window for obtaining a local deviation image of i-th index is (i+2) by (i+2). Here, the range of the indices is {0, 1, 2, -, (R-3), (R-2), and (R-l)}. The local deviation images created by the local deviation image creating unit 12 are provided to the intensity equalization unit 14.
[31] The intensity equalization unit 14 includes the same number of maximum filters 31,
33, ... and 35 as that of the local deviation calculators 21, 23, ... and 25. The maximum filters 31, 33, ... and 35 have different sizes of windows 32, 34, ..., and 36 allocated thereto and equalize the widths with high intensities in the deviation images provided from the corresponding local deviation calculators 21, 23, ..., and 25, respectively.
[32] If a local deviation image is obtained using a two-dimensional image, it is observed that the intensity for the local deviation image will increase owing to a patterned portion in the two-dimensional image. The reason why is that the pixels included in the
patterned pattern have different intensities with each other, and thus the deviation for the local deviation image becomes increase. On the other hand, when several local deviation images are obtained by applying several sizes of windows to a two- dimensional image, respectively, width of a portion with a high intensity becomes different for each local deviation image. In other words, when obtaining a local deviation image by applying a small sized window, a portion with a high intensity in the local deviation image has a thin width. On the contrary, when obtaining a local deviation image by applying a large sized window, a portion with a high intensity in the local deviation image has a thick width.
[33] The maximum filters 31, 33, ..., 35 are used to equalize the widths of the portions with high intensities in the local deviation images, respectively. The maximum filters select the maximum values of the pixels in the windows applied to the local deviation images, so that portions with high intensities in the local deviation images are made thicker.
[34] In this regard, the degree by which a portion with a high intensity in a local deviation image makes thicker in width thereof can be adjusted by making the sizes of windows different from each other. In other words, if the size of a window used in a maximum filter is small, the degree by which a portion with a high intensity in a local deviation image becomes thicker is very small. On the contrary, if the size of a window used in a maximum filter is large, the degree by which a portion with a high intensity in a local deviation image becomes thicker is increased.
[35] Therefore, according to the embodiment of the present invention, a rule is applied when the sizes of windows used in maximum filters are determined. In other words, when windows of different sizes are allocated to the maximum filters, respectively, the windows are sequentially applied from the one of the largest size to the one of the smallest size opposite to the sequence of allocation of the sizes of windows by the deviation calculators.
[36] The following table represents the relationship between the window sizes employed in the local deviation calculators and the maximam filters and indices.
[37] Table 1
[Table 1]
[38] The window size having an i-th index for obtaining an equalized deviation image from a maximum filter is (R-i) by (R-i). Here, the range of the indices is {0, 1, 2, •••, (R-3), (R-2), and (R-l)}. For example, the local deviation image to which a 2 by 2 window is applied is equalized by a maximum filter having the window size of 10 by 10. Accordingly, the equalized images are obtained by applying local deviations and maximum filtering in a single two-dimensional image. The equalized deviation images created by the maximum filters are provided to the depth map creating unit 16.
[39] The depth map creating unit 16 creates a depth map by using the equalized deviation images provided from the intensity equalization unit 14. In the depth map, the intensities of pixels represent absolute distances between points on an object and a focal plane, respectively. In the depth map creation unit 16, the depth map is obtained by comparing the intensities of pixels in the equalized deviation images at the same image coordinates.
[40] Pixel values equalized by the same number of maximum filters as the depth resolutions R exist in one image coordinate. Once again, the depth map creation unit 16 compares the intensities of the pixels, selects a largest pixel among them and determines which index the largest pixel is located at.
[41] In other words, assuming that the resultant of the maximum filter is fj(x,y) in (x,y) coordinate of the maximum filter when the i-th window size is applied to a two- dimensional image, a value d(x,y) of the depth map in the (x,y) coordinate is expressed as d(x,y) =
However, in such an approach, the results of maximum filters are simply compared in the same pixel coordinates, and the comparison results are merely used to find the index where the maximum pixel value is located. Ac-
cordingly, the values of respective pixels in the depth map cause acquisition of an inaccurate depth map since they are not influenced by the depth map values of peripheral pixels.
[42] Therefore, the embodiment of the present invention employs a belief propagation algorithm in the depth map creation unit 16 to solve the above-mentioned disadvantages. The belief propagation algorithm enables acquisition of a depth map by using a plurality of equalized images obtained by the filter module 14. A process to obtain a depth map in the depth map creation unit 16 is the same that of described above, that is, the depth map is also obtained by comparing intensities of equalized images in the same image coordinates. At the same time, the belief propagation algorithm allows adjacent pixels to have similar depth map values to thereby obtain a more accurate depth map.
[43] The respective pixel values of the depth map created by the depth map creation unit
16 represent how far the object is located from a focused object. In other words, when the pixel values in a depth map are small, the distance between a target object and a focused object is small, and otherwise, larger.
[44] As mentioned above, according to the present invention, depths for respective pixels can be estimated from a single two-dimensional image, and depth information can be obtained by processing depth estimating operations in parallel.
[45] While the invention has been shown and described with respect to the exemplary embodiment, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the scope of the invention as defined in the following claims.
[46]
Claims
[1] A method for estimating depths for pixels in a single two-dimensional image, the method comprising: creating local deviation images by applying different sizes of windows to the two-dimensional image; creating equalized images by applying windows of different sizes to the respective local deviation images and equalizing portions of the respective local deviation images that have different intensities; and creating a depth map using the equalized deviation images.
[2] The method of claim 1, wherein creating the local deviation images and creating the equalized images includes applying the respective windows in parallel to create the local deviation images and the equalized deviation images.
[3] The method of claim 1, wherein, in creating the local deviation images and creating the equalized images, the sizes of the windows become gradually different.
[4] The method of claim 3, wherein the sizes of the windows applied to the respective local deviation images, are opposite to the sizes of the windows applied during creation of the respective equalized images.
[5] The method of claim 1, wherein a belief propagation algorithm is used to create the depth map.
[6] The method of claim 1, wherein the number of windows applied during creation of the local deviation images is set to the same number as depth resolutions of the two-dimensional image.
[7] The method of claim 1, wherein the number of windows applied during creation of the equalized images is set to the same number as depth resolutions of the two-dimensional image.
[8] A depth estimation apparatus comprising: a local deviation image creation unit for creating local deviation images by applying windows of different sizes to a single two-dimensional image applied thereto; an intensity equalization unit for creating equalized deviation images by applying windows of different sizes to the local deviation images and equalizing portions of the local deviation images that have different intensities; and a depth map creation unit for creating a depth map using the equalized deviation images.
[9] The apparatus of claim 8, wherein the local deviation creating unit includes local deviation calculators having windows of different sizes, respectively, wherein
each local deviation calculators creates a local deviation image by applying a window allocated thereto to the two-dimensional image, by calculating a deviation for pixels in the window, and by applying the calculated deviation to the pixels in the two-dimensional image.
[10] The apparatus of claim 9, wherein the intensity equalization unit includes maximum filters having different windows, respectively, wherein each maximum filters creates an equalized deviation image by applying a window allocated thereto to the local deviation image from the corresponding local deviation calculator and by equalizing a portion in the local deviation image that has different intensity.
[11] The apparatus of claim 8, wherein the local deviation image creation unit and the intensity equalization unit perform in parallel to create the respective local deviation images and the equalized images, respectively.
[12] The apparatus of claim 8, wherein the local deviation calculators and the maximum filters use windows the sizes of which become gradually different.
[13] The apparatus of claim 12, wherein the sizes of the windows allocated to the local deviation calculators, respectively, are opposite to the sizes of the windows allocated to the maximum filters, respectively.
[14] The apparatus of claim 8, wherein the depth map creation unit creates the depth map using a belief propagation algorithm.
[15] The apparatus of claim 8, wherein the number of windows allocated to the local deviation calculators is set to the same value as depth resolutions of the two- dimensional image.
[16] The apparatus of claim 8, wherein the number of windows allocated to the maximum filters is set to the same value as depth resolutions of the two- dimensional image.
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| US8743180B2 (en) | 2011-06-28 | 2014-06-03 | Cyberlink Corp. | Systems and methods for generating a depth map and converting two-dimensional data to stereoscopic data |
| EP2747028A1 (en) | 2012-12-18 | 2014-06-25 | Universitat Pompeu Fabra | Method for recovering a relative depth map from a single image or a sequence of still images |
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