Plane Sweep Stereo
Implement a plane sweep stereo algorithm for multi-view stereo, a technique used in depth estimation to calculate the depth of a scene from multiple images. This task involves sweeping a series of depth planes through the scene to estimate the depth at each point.
The concept of plane sweep stereo relies on the idea of homography, which describes the transformation between two images of the same planar scene. For a given depth plane, the homography matrix H can be used to warp all images to a reference view. The photo-consistency of the warped images is then computed, typically using the variance of the pixel values.
Here are the general steps to follow:
- Define a series of depth planes to sweep through the scene
- For each depth plane, compute the homography matrix H and warp all images to the reference view
- Compute the photo-consistency of the warped images
This technique is widely used in computer vision applications, such as 3D reconstruction and robotics.
Example:
Multiple images and poses
Depth map
For each depth, warp images and check consistency
Constraints:
- Input images: 3D numpy arrays (color or grayscale) with shape (height, width, channels) and pixel values in [0, 255]
- Input poses: 2D numpy arrays with shape (num_views, 4, 4) representing the camera transformation matrices
- Valid depth range: [0, 100] meters, with a minimum and maximum depth plane distance of 0.1 and 10 meters respectively
- Output depth map: 2D numpy array with shape (height, width) and pixel values representing the estimated depth in meters, returned as float32 numpy array
- Assumption: All input images are already undistorted and have the same intrinsic camera parameters