Automatic detection of stereoscopic content in video/image data
A method includes calculating, through a processor of a computing device communicatively coupled to a memory, correlation between two portions of an image and/or a video frame on either side of a reference portion thereof. The method also includes determining, through the processor, whether content of the image and/or the video frame is stereoscopic or non-stereoscopic based on the determined correlation.
1. A method comprising:
calculating, utilizing a processor, a correlation between two portions of an image created by dividing the image utilizing a vertical reference edge, including determining for each of a plurality of rows of the image an offset between the two portions of the image, and calculating an average offset for the image by averaging the plurality of offsets for the plurality of rows; and
determining whether the image is stereoscopic by calculating a sample variance of the plurality of offsets, and determining that the image is stereoscopic if the sample variance is below a predetermined threshold value.
2. The method of claim 1 , further comprising detecting the vertical reference edge by performing high-pass filtering.
3. The method of claim 1 , further comprising; determining a directional distribution of peak amplitude values for each of a plurality of rows of the image, and determining an eye parity between the two portions of the image, utilizing the directional distribution of the peak amplitude values.
4. A computing device comprising:
a memory; and
a processor communicatively coupled to the memory, the processor being configured to execute instructions for:
calculating, utilizing a processor, a correlation between two portions of an image created by dividing the image utilizing a vertical reference edge, including determining for each of a plurality of rows of the image an offset between the two portions of the image, and calculating an average offset for the image by averaging the plurality of offsets for the plurality of rows; and
determining whether the image is stereoscopic by calculating a sample variance of the plurality of offsets, and determining that the image is stereoscopic if the sample variance is below a predetermined threshold value.
5. A non-transitory medium, readable through a computing device and including instructions embodied therein that are executable through the computing device, comprising instructions for:
calculating, utilizing a processor, a correlation between two portions of an image created by dividing the image utilizing a vertical reference edge, including determining for each of a plurality of rows of the image an offset between the two portions of the image, and calculating an average offset for the image by averaging the plurality of offsets for the plurality of rows; and
determining whether the image is stereoscopic by calculating a sample variance of the plurality of offsets, and determining that the image is stereoscopic if the sample variance is below a predetermined threshold value.
6. The computing device of claim 4 , further comprising detecting the vertical reference edge by performing high-pass filtering.
7. The computing device of claim 4 , further comprising, determining a directional distribution of peak amplitude values for each of a plurality of rows of the image, and determining an eye parity between the two portions of the image, utilizing the directional distribution of the peak amplitude values.
8. The non-transitory medium of claim 5 , further comprising detecting the vertical reference edge by performing high-pass filtering.
9. The non-transitory medium of claim 5 , further comprising, determining a directional distribution of peak amplitude values for each of a plurality of rows of the image, and determining an eye parity between the two portions of the image, utilizing the directional distribution of the peak amplitude values.