公开(公告)号：SG11201811330WA

公开(公告)日：2019-01-30

申请号：SG11201811330W

申请日：2017-06-09

Applicant: IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE

Inventor： MCCORMAC JOHN BRENDAN ,  HANDA ANKUR ,  DAVISON ANDREW ,  LEUTENEGGER STEFAN

IPC: G06F17/00 ,  G06K9/00 ,  G06K9/62

Abstract: Certain examples described herein enable semantically-labelled representations of a three-dimensional (3D) space to be generated from video data. In described examples, a 3D representation is a surface element or ‘surfel’ representation, where the geometry of the space is modelled using a plurality of surfaces that are defined within a 3D co-ordinate system. Object-label probability values for spatial elements of frames of video data may be determined using a two-dimensional image classifier. Surface elements that correspond to the spatial elements are identified based on a projection of the surface element representation using an estimated pose for a frame. Object-label probability values for the surface elements are then updated based on the object-label probability values for corresponding spatial elements. This results in a semantically-labelled 3D surface element representation of objects present in the video data. This data enables computer vision and/or robotic applications to make better use of the 3D representation.

公开(公告)号：AU2016313849A1

公开(公告)日：2018-03-08

申请号：AU2016313849

申请日：2016-08-23

Applicant: IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE

Inventor： LUKIERSKI ROBERT ,  LEUTENEGGER STEFAN ,  DAVISON ANDREW

IPC: G06T7/00

Abstract: Certain examples described herein relate to mapping a space using a multi-directional camera. This mapping may be performed in relation to a robotic device comprising a monocular multi-directional camera device and at least one movement actuator. The mapping may generate an occupancy map to determine navigable portions of the space. In examples, a movement of the robotic device around a point in a plane of movement is instructed using the at least one movement actuator. Using the monocular multi- directional camera device, a sequence of images are then obtained (610) at a plurality of different angular positions during the instructed movement. Pose data is determined (620) from the sequence of images. The pose data is determined using a set of features detected within the sequence of images. Depth values are then estimated (630) by evaluating a volumetric function of the sequence of images and the pose data. The depth values are processed (640) to populate the occupancy map for the space.