MSc dissertation proposal 2019/2020

Visual Anticipation of Collisions with Moving Objects

Introduction:

Plenoptic cameras allow to estimate 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 modelling and calibration.

2) Self-Motion estimation using the camera geometry.

3) Estimating the motion of moving objects.

Detailed description:

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.

The workplan consists on the study of the plenoptic camera model and calibration, and implementation of a standard depth estimation algorithm for conventional and plenoptic cameras.

More MSc dissertation proposals on Computer and Robot Vision in:

http://omni.isr.ist.utl.pt/~jag