Objectives:
Plenoptic cameras
allow estimating depth from a single image by analysis of their epipolar geometry. Combining depth and motion estimation allows
anticipating where a moving object may be in a collision course with the
camera.
The objectives of
this work are:
1) Plenoptic
camera model definition and calibration.
2) Depth range
limits definition for a plenoptic camera.
3) Depth
estimation using the camera epipolar geometry.
4) Mosaicking and 3D reconstruction and comparison with
standard methods.
Requirements (grades, required courses, etc):
--
Localization:
ISR / IST
Observations:
Typical strategies
to obtain a 3D reconstruction are based on shape from motion and shape from
shading. 3D reconstruction is usually challenging due to the need of
integrating large amounts of data within a short frame of time. Plenoptic
cameras give more information than conventional cameras. Namely, these cameras
give information about the direction and contribution of each ray to the total
amount of light captured on an image. These cameras allow to
estimate depth from a single image by analysis of their epipolar geometry, which may allow to overcome some of the
current limitations of conventional cameras.
Plenoptic cameras
make a trade-off between spatial and angular resolution which normally results
in images with low spatial resolution. To overcome this limitation we aim to
create a lightfield mosaic and perform a 3D
reconstruction.
The workplan consists on the study of the plenoptic
camera model and calibration, and implementation of a standard mosaicking and depth estimation algorithms for conventional
and plenoptic cameras. These methods will be applied to
real datasets. The results for the plenoptic camera
will be compared to the results from a conventional camera.
More information about this
project:
http://users.isr.ist.utl.pt/~jag/msc/msc_2017_2018.html