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      Out of Sight But Not Out of Mind: An Answer Set Programming Based Online Abduction Framework for Visual Sensemaking in Autonomous Driving

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          Abstract

          We demonstrate the need and potential of systematically integrated vision and semantics} solutions for visual sensemaking (in the backdrop of autonomous driving). A general method for online visual sensemaking using answer set programming is systematically formalised and fully implemented. The method integrates state of the art in (deep learning based) visual computing, and is developed as a modular framework usable within hybrid architectures for perception & control. We evaluate and demo with community established benchmarks KITTIMOD and MOT. As use-case, we focus on the significance of human-centred visual sensemaking ---e.g., semantic representation and explainability, question-answering, commonsense interpolation--- in safety-critical autonomous driving situations.

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          Most cited references9

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          Are we ready for autonomous driving? The KITTI vision benchmark suite

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            Maintaining knowledge about temporal intervals

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              Simple online and realtime tracking

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                Author and article information

                Journal
                31 May 2019
                Article
                1906.00107
                0fd9b612-a5be-45ef-99b9-5f6396d1cb2c

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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                Custom metadata
                IJCAI 2019: the 28th International Joint Conference on Artificial Intelligence (IJCAI) 2019, August 10 - 16, Macao. (Preprint / to appear)
                cs.AI cs.CV cs.LO

                Computer vision & Pattern recognition,Theoretical computer science,Artificial intelligence

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