Creating a model tree using group tokens for identifying objects in an image

A machine-readable medium encoded with instructions, that when executed by a processor, cause the processor to carry out a process for identifying objects in images, comprising:

• computing one or more interest points in each of a plurality of training images including one or more objects, wherein each interest point represents one pixel, and wherein the one or more interest points in a training image represent a subset of the pixels of the training image;
• extracting tokens associated with the interest points, wherein a token associated with an interest point comprises an image feature of an image region surrounding the interest point;
• comparing tokens associated with an interest point in a first training image with tokens associated with an interest point in a second training image to find matched tokens, wherein a matched token comprises a first token in the first training image and a second token in the second training image, and wherein the first token is related to the second token;
• grouping the matched tokens into sets, wherein a set comprises related matched tokens;
• computing a group token to represent each set of matched tokens;
• and
• creating a model tree using the group tokens, where each node of the tree represents an object model for identifying objects in images.

A hardware system for identifying objects in images, comprising:

• an interest point locator module for computing one or more interest points in each of a plurality of training images including one or more objects, wherein each interest point represents one pixel, and wherein the one or more interest points in a training image represent a subset of the pixels of the training image;
• a token extraction module for extracting tokens associated with the interest points, wherein a token associated with an interest point comprises an image feature of an image region surrounding the interest point;
• a token grouping module for comparing tokens associated with an interest point in a first training image with tokens associated with an interest point in a second training image to find matched tokens, wherein a matched token comprises a first token in the first training image and a second token in the second training image, and wherein the first token is related to the second token, for grouping the matched tokens into sets, wherein a set comprises related matched tokens, and for computing a group token to represent each set of matched tokens;
• and
• a model tree creator module for creating a model tree using the group tokens, where each node of the tree represents an object model for identifying objects in images.

A hardware system for identifying objects in images, comprising:

• a means for computing one or more interest points in each of a plurality of training images including one or more objects, wherein each interest point represents one pixel, and wherein the one or more interest points in a training image represent a subset of the pixels of the training image;
• a means for extracting tokens associated with the interest points, wherein a token associated with an interest point comprises an image feature of an image region surrounding the interest point;
• a means for comparing tokens associated with an interest point in a first training image with tokens associate with an interest point in a second training image to find matched tokens, wherein a matched token comprises a first token in the first training image and a second token in the second training image, and wherein the first token is related to the second token, for grouping the matched tokens into sets, wherein a set comprises related matched tokens, and for computing a group token to represent each set of matched tokens;
• and
• a means for creating a model tree using the group tokens, where each node of the tree represents an object model for identifying objects in images.