| Autor: |
Jeremy F. Burn, G. P. Daniels, David Bull |
| Rok vydání: |
2015 |
| Předmět: |
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| Zdroj: |
ICIP |
| DOI: |
10.1109/icip.2015.7350950 |
| Popis: |
During locomotion, Autonomous Ground Vehicles (AGV) need to map the surface of the ground ahead in order to plan a safe route of passage. Algorithms that achieve this are all derived from a basic requirement to track pixels between successive frames. This paper establishes the effect of tracking error on depth estimation with different image-plane geometries and presents an argument for tight control of the camera orientation. It is found that the effect of tracking error is invariant with camera angle for a concave image-plane but varies non-linearly with angle for both flat and inverse-flat image-planes. Pairs of frames are produced by each camera from a simulated scene and a selection of algorithms are used to compute the optical flow. It is shown that current state-of-the-art optical flow algorithms can successfully track pixels across concave and inverse-flat image-planes. This results in comparable depth estimation accuracy to a flat image-plane but allows for improved object tracking. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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