Continuous depth map reconstruction
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This paper presents a novel method to reconstruct continuous depth maps from light field data by solving a linear system. Conventional approaches treat depth map reconstruction as an optimization problem with discrete labels. The proposed method extracts raw depth information and confidence levels from the light field data using structure tensor. It also introduces a method to reduce the adverse effect of unreliable local estimations, helping to eliminate errors in specular areas and edges where depth values change abruptly. Experiments on synthetic and real light field data demonstrate the effectiveness of the proposed continuous depth map reconstruction method.
Continuous depth map reconstruction
- 1. Continuous Depth Map Reconstruction From Light Fields Abstract: Light field analysis recently received growing interest, since its rich structure information benefits many computer vision tasks. This paper presents a novel method to reconstruct continuous depth maps from light field data. Conventional approaches usually treat depth map reconstruction as an optimization problem with discrete labels. On the contrary, our proposed method can obtain continuous depth maps by solving a linear system, which preserves richer details compared with conventional discrete approaches. Structure tensor is employed to extract raw depth information and corresponding confidence levels from the light field data. We introduce a method to reduce the adverse effect of unreliable local estimations, which helps to get rid of errors in specula areas and edges where depth values are discontinuous. Experiments on both synthetic and real light field data demonstrate the effectiveness of the proposed method. Existing System : Light field analysis recently received growing interest, since its rich structure information benefits many computer vision tasks This paper presents a novel method to reconstruct continuous depth maps from light field data. Conventional approaches usually treat depth map reconstruction as an optimization problem with discrete labels DISADVANTAGES OF EXISTING SYSTEM : . It will not Generates more accurate Depth values and tends to keep more detail. .it has optimization problem.
- 2. ProposedSystem: Our proposed method can obtain continuous depth maps by solving a linear system, which preserves richer details compared with conventional discrete approaches. Structure tensor is employed to extract raw depth information and corresponding confidence levels from the light field data. We introduce a method to reduce the adverse effect of unreliable local estimations, which helps to get rid of errors in specula areas and edges where depth values are discontinuous. Experiments on both synthetic and real light field data demonstrate the effectiveness of the proposed method. Advantages of proposed system: .Reduce the adverse effect of unreliable local estimations. .Errors inspeculaareasand edgeswhere depthvaluesare discontinuous . .Preserves richer details compared with conventional discrete approaches. SOFTWARE AND HARDWARE REQUIREMENT System requirements: Operating system : Windows XP/7. Coding Language : MATLAB Tool : MATLAB R 2012 HARDWARE REQUIREMENTS: System : Pentium IV 2.4 GHz. Hard Disk : 40 GB. Floppy Drive : 1.44 Mb.
- 3. Monitor : 15 VGA Colour. Mouse : Logitech. Ram : 512 Mb.