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Author  |
Daniel Hernandez; Lukas Schneider; Antonio Espinosa; David Vazquez; Antonio Lopez; Uwe Franke; Marc Pollefeys; Juan C. Moure | ||||
| Title | Slanted Stixels: Representing San Francisco's Steepest Streets} | Type | Conference Article | ||
| Year | 2017 | Publication | 28th British Machine Vision Conference | Abbreviated Journal | |
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| Abstract | In this work we present a novel compact scene representation based on Stixels that infers geometric and semantic information. Our approach overcomes the previous rather restrictive geometric assumptions for Stixels by introducing a novel depth model to account for non-flat roads and slanted objects. Both semantic and depth cues are used jointly to infer the scene representation in a sound global energy minimization formulation. Furthermore, a novel approximation scheme is introduced that uses an extremely efficient over-segmentation. In doing so, the computational complexity of the Stixel inference algorithm is reduced significantly, achieving real-time computation capabilities with only a slight drop in accuracy. We evaluate the proposed approach in terms of semantic and geometric accuracy as well as run-time on four publicly available benchmark datasets. Our approach maintains accuracy on flat road scene datasets while improving substantially on a novel non-flat road dataset. | ||||
| Address | London; uk; September 2017 | ||||
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| Area | Expedition | Conference | BMVC | ||
| Notes | ADAS; 600.118 | Approved | no | ||
| Call Number | ADAS @ adas @ HSE2017a | Serial | 2945 | ||
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