CONTOUR-BASED CLASSIFICATION OF OBJECTS

摘要

Described herein is a contour-based method of classifying an item, such as a physical object or pattern. In an example method, a one-dimensional (1D) contour signal is received for an object. The one-dimensional contour signal comprises a series of 1D or multi-dimensional data points (e.g. 3D data points) that represent the contour (or outline of a silhouette) of the object. This 1D contour can be unwrapped to form a line, unlike for example, a two-dimensional signal such as an image. Some or all of the data points in the 1D contour signal are individually classified using a classifier which uses contour-based features. The individual classifications are then aggregated to classify the object and/or part(s) thereof. In various examples, the object is an object depicted in an image.