| 摘要 |
A method and system for detecting objects within a three-dimensional (3D) environment, comprising obtaining a 3D point-cloud representation of the environment, the point-cloud comprising a set of point locations, and converting the point-cloud to a 3D feature grid, wherein converting the point-cloud to the 3D feature grid comprises discretising the 3D space into cells according to a grid size; determining which cells contain points from the 3D point-cloud; and mapping any that do to a feature vector; and mapping any that do not to a zero feature vector. The method further comprises generating a detection window sized to contain an integral number of the cells and having a set of positions which can be occupied; calculating a detection score for each of the positions by: casting a vote for each cell within the detection window into which at least one point falls, wherein each vote is calculated using the feature vector of the cell and a weighting vector; and summing the votes, and determining whether each position contains an object of interest based on the detection score, each detection window with a detection score greater than a threshold being classified as containing an object of interest. |
