Abstract:
A depth map is generated from at least a first and a second image. A plurality of reference pixels are selected in the first image. A cost function is used to associate each reference pixel with a respective pixel in the second image. A masking operation is used to identify a subset of pixels in a block of pixels surrounding a reference pixel and the cost function is based on the identified subset of pixels. A disparity between each reference pixel and the respective pixel in said second image is determined, and a depth value is determined for each reference pixel as a function of the respective disparity. A depth map is generated based on the determined depth values.
Abstract:
Disclosed herein is a laser projection system including a laser projector emitting a laser beam, a movable mirror apparatus reflecting the laser beam toward a surface, and a graphics processing unit (GPU). The GPU is configured to receive video data, estimate a varying speed of movement of the movable mirror apparatus for different positions of the laser beam across the surface, and process the video data based upon the estimated varying speed of movement. An application specific integrated circuit (ASIC) receives the processed video data, and to generate a beam position control signal based upon required or desired movement of the movable mirror apparatus. A laser driver controls the laser projector as a function of the processed video data, and a mirror controller controls the movable mirror apparatus as a function of the beam position control signal.
Abstract:
A depth map is generated from at least a first and a second image. A plurality of reference pixels in the first image are selected and associated with respective pixels in the second image. A disparity between each reference pixel and the respective pixel in said second image is determined, and a depth value is determined as a function of the respective disparity. The plurality of reference pixels is selected based on detected contours in the first image.
Abstract:
A depth map is generated from at least a first and a second image. A plurality of reference pixels in the first image are selected and associated with respective pixels in the second image. A disparity between each reference pixel and the respective pixel in said second image is determined, and a depth value is determined as a function of the respective disparity. The plurality of reference pixels is selected based on detected contours in the first image.
Abstract:
A depth map is generated from at least a first and a second image. Generally, a plurality of reference pixels are selected in the first image and associated with respective pixels in the second image. Next, the disparity between each reference pixel and the respective pixel in said second image is determined, and for each reference pixel a depth value as a function of the respective disparity. In particular, each reference pixel is associated with a respective pixel in the second image via a matching and a filtering operation. The matching operation selects for each reference pixel a plurality of candidate pixels in the second image and associates with each candidate pixel a respective cost function value and a respective disparity value.
Abstract:
A depth map is generated from at least a first and a second image. A plurality of reference pixels are selected in the first image. A cost function is used to associate each reference pixel with a respective pixel in the second image. A masking operation is used to identify a subset of pixels in a block of pixels surrounding a reference pixel and the cost function is based on the identified subset of pixels. A disparity between each reference pixel and the respective pixel in said second image is determined, and a depth value is determined for each reference pixel as a function of the respective disparity. A depth map is generated based on the determined depth values.