• Corpus ID: 211010598

Depth Map Estimation of Dynamic Scenes Using Prior Depth Information

  title={Depth Map Estimation of Dynamic Scenes Using Prior Depth Information},
  author={James Noraky and Vivienne Sze},
Depth information is useful for many applications. Active depth sensors are appealing because they obtain dense and accurate depth maps. However, due to issues that range from power constraints to multi-sensor interference, these sensors cannot always be continuously used. To overcome this limitation, we propose an algorithm that estimates depth maps using concurrently collected images and a previously measured depth map for dynamic scenes, where both the camera and objects in the scene may be… 
2 Citations


Dense Depth Estimation of a Complex Dynamic Scene without Explicit 3D Motion Estimation
This work shows that, given per-pixel optical flow correspondences between two consecutive frames and, the sparse depth prior for the reference frame, it can effectively recover the dense depth map for the successive frames without solving for 3D motion parameters.
Dense Monocular Depth Estimation in Complex Dynamic Scenes
A novel motion segmentation algorithm is provided that segments the optical flow field into a set of motion models, each with its own epipolar geometry, and it is shown that the scene can be reconstructed based on these motion models by optimizing a convex program.
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Low Power Depth Estimation of Rigid Objects for Time-of-Flight Imaging
  • J. Noraky, V. Sze
  • Computer Science
    IEEE Transactions on Circuits and Systems for Video Technology
  • 2020
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