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Published byHayden Eames Modified over 9 years ago
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Prof. S. Pulman P. Blunsom N.T. Crook
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Seek to combine Computer Vision with Natural Language Processing for applications in intelligent transport systems. * Driver assisted technology using in-car speech systems for * Hazard avoidance * verbal warnings of potential hazards that have been perceived by video cameras around the vehicle System: “A pedestrian has stepped out onto the road from the left” * Route planning & navigation * Enhancing the output of navigation devices using landmarks and other visible reference objects System: “Turn left after the post-box on the corner” * Clarification of navigation instructions System: “Take the next left” Driver: “Is that after the post-office van that is parked on the right?” * En route renegotiation of planned route Driver: “I need to get some money out from a cash machine, is there one nearby?”
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* Driver assisted technology “A car has pulled out onto the carriageway in front of you.” “There is a car in the on-coming carriageway waiting to turn into the junction on the left.” “A cyclist is crossing the carriageway ahead.”
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* Extract 3D relations from 2D image * Some relations are dependent on where the objects are in the image and whether the referent object has a direction “The cyclist is behind the car” “The car is behind the van” the van is the referent object which is facing towards the camera
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* Descriptions generated from images in the test set “The Bicylist is front left of the Car” “The Bicylist is next to the Pedestrian” “The Pedestrian is on the Road”
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“The Car is behind the SUVPickupTruck” “The SUVPickupTruck is in front of the Car” “The Car is at the TrafficLight”
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“The SUVPickupTruck is in front of the Car” “The Car is in front of the Truck_Bus”
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