Method for predicting stereoscopic depth and apparatus thereof
First Claim
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1. A method for predicting stereoscopic depth, comprising:
- capturing object images of a target scene;
generating a stereoscopic depth image associated with the object images;
identifying a no-depth-data region in the stereoscopic depth image;
identifying a depth-data region correlated to the no-depth-data region; and
assigning a depth data to the no-depth-data region based on a depth data of the depth-data region correlated to the no-depth-data region;
wherein identifying the depth-data region correlated to the no-depth-data region comprises;
categorizing the object image of the target scene into a plurality of categorized pixel blocks based on image characteristics in the object image; and
searching through the plurality of categorized pixel blocks to identify a first pixel block associated with a no-depth-data region; and
wherein the plurality of categorized pixel blocks are categorized based on one or a combination of image characteristics selected from color, grey scale, texture, contour, and shape.
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Abstract
The present application discloses a method for predicting stereoscopic depth comprising capturing object images of a target scene; generating a stereoscopic depth image associated with the object images; identifying a no-depth-data region in the stereoscopic depth image; identifying a depth-data region correlated to the no-depth-data region; and assigning a depth data to the no-depth-data region based on a depth data of the depth-data region correlated to the no-depth-data region.
8 Citations
20 Claims
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1. A method for predicting stereoscopic depth, comprising:
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capturing object images of a target scene; generating a stereoscopic depth image associated with the object images; identifying a no-depth-data region in the stereoscopic depth image; identifying a depth-data region correlated to the no-depth-data region; and assigning a depth data to the no-depth-data region based on a depth data of the depth-data region correlated to the no-depth-data region; wherein identifying the depth-data region correlated to the no-depth-data region comprises; categorizing the object image of the target scene into a plurality of categorized pixel blocks based on image characteristics in the object image; and searching through the plurality of categorized pixel blocks to identify a first pixel block associated with a no-depth-data region; and wherein the plurality of categorized pixel blocks are categorized based on one or a combination of image characteristics selected from color, grey scale, texture, contour, and shape. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 14, 15, 16)
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12. A method for predicting stereoscopic depth, comprising:
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capturing object images of a target scene; generating a stereoscopic depth image associated with the object images; identifying a no-depth-data region in the stereoscopic depth image; identifying a depth-data region correlated to the no-depth-data region; and assigning a depth data to the no-depth-data region based on a depth data of the depth-data region correlated to the no-depth-data region; wherein identifying the depth-data region correlated to the no-depth-data region comprises; categorizing the object image of the target scene into a plurality of categorized pixel blocks based on image characteristics in the object image; generating a partition table storing positional information of each pixel in the plurality of categorized pixel blocks; calculating a correlation strength between each two adjacent pixel blocks among the plurality of categorized pixel blocks, the two adjacent pixel blocks are identified by searching through the partition table; and searching through the plurality of categorized pixel blocks to identify a first pixel block associated with a no-depth-data region; and wherein the correlation strength is calculated based on a similarity of average grey scale level between each two adjacent pixel blocks among the plurality of categorized pixel blocks. - View Dependent Claims (13, 18, 19, 20)
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17. A method for predicting stereoscopic depth, comprising:
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capturing object images of a target scene; generating a stereoscopic depth image associated with the object images; identifying a no-depth-data region in the stereoscopic depth image; identifying a depth-data region correlated to the no-depth-data region; and assigning a depth data to the no-depth-data region based on a depth data of the depth-data region correlated to the no-depth-data region; wherein identifying the depth-data region correlated to the no-depth-data region comprises; categorizing the object image of the target scene into a plurality of categorized pixel blocks based on image characteristics in the object image; generating a partition table storing positional information of each pixel in the plurality of categorized pixel blocks; calculating a correlation strength between each two adjacent pixel blocks among the plurality of categorized pixel blocks, the two adjacent pixel blocks are identified by searching through the partition table; searching through the plurality of categorized pixel blocks to identify a first pixel block associated with a no-depth-data region; identifying a most relevant pixel block correlated to the first pixel block associated with the no-depth-data region based on the correlation strength between each two adjacent pixel blocks; and assigning a depth-data region associated with the most relevant pixel block as the depth-data region correlated to the no-depth-data region; wherein assigning the depth data to the no-depth-data region based on the depth data of the depth-data region correlated to the no-depth-data region comprises; obtaining an average value of the depth data for the one or more depth-data regions in the most relevant pixel block; and assigning the average value as the depth data for the no-depth-data region; and wherein assigning the depth data to the no-depth-data region based on the depth data of the depth-data region correlated to the no-depth-data region comprises; obtaining an average value of the grey scale levels for the one or more depth-data regions in the most relevant pixel block; and assigning the average value of the grey scale levels as the depth data for the no-depth-data region.
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Specification