2008
DOI: 10.1016/j.micpro.2007.10.002
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Real-time disparity map computation module

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Cited by 43 publications
(38 citation statements)
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“…In (Georgoulas et al, 2008) the disparity map is computed using an adaptive technique where the support window for each pixel is selected according to the local variation over it. This technique enables less false correspondences during the matching process while preserving high image detail in regions with low texture and among edges.…”
Section: Resultsmentioning
confidence: 99%
See 2 more Smart Citations
“…In (Georgoulas et al, 2008) the disparity map is computed using an adaptive technique where the support window for each pixel is selected according to the local variation over it. This technique enables less false correspondences during the matching process while preserving high image detail in regions with low texture and among edges.…”
Section: Resultsmentioning
confidence: 99%
“…The work by (Georgoulas et al, 2008), presents a hardware-efficient real-time disparity map computation system. A modified version of the SAD-based technique is imposed, using an adaptive window size for the disparity map computation.…”
Section: Sad-based Disparity Computation With Ca Post-filteringmentioning
confidence: 99%
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“…This system can produce 640 x 480 dense disparity maps with 64 levels of disparity at 30 FPS and has an estimated cost of $2,582 dollars. Two systems able to process more than 200 images per second, are presented by Georgoulas et al (Georgoulas et al (2008)) and Jin et al (Jin et al (2010)) respectively. The first system used SAD and the second is based on Census for computing the disparity map, both system process 640 x 480 images and both of them have a price higher than a thousand dollars.…”
Section: Real Time Stereovision: State Of the Artmentioning
confidence: 99%
“…The first is to employ the information from a pair of synchronized stereo images as presented in [7,8]. The point-by-point matching between the two images can be used to generate a depth map.…”
Section: Depth Map Generationmentioning
confidence: 99%