Abstract:
Disclosed is a method and apparatus for exemplars-based color classification. In one embodiment, the functions implemented include: processing an image captured by a camera to identify a first color profile that most closely matches colors of the image, wherein the first color profile is selected from a plurality of color profiles each color profile encoding data related to how two or more component colors appear under a different lighting condition.
Abstract:
A computer-implemented method of tracking a target object in an object recognition system includes acquiring a plurality of images with a camera and simultaneously tracking the target object and dynamically building online map data from the plurality of images. Tracking of the target object is based on the online map data and the offline map data. In one aspect, tracking the target object includes enabling only one of the online map data and offline map data for tracking based on whether tracking is successful. In another aspect, tracking the target object includes fusing the online map data with the offline map data to generate a fused online model.
Abstract:
A method of building a database for an object recognition system includes acquiring several multi-view images of a target object and then extracting a first set of features from the images. One of these extracted features is then selected and a second set of features is determined based on which of the first set of features include both, descriptors that match and keypoint locations that are proximate to the selected feature. If a repeatability of the selected feature is greater than a repeatability threshold and if a discriminability is greater than a discriminability threshold, then at least one derived feature is stored to the database, where the derived single feature is representative of the second set of features.