Producing object cutouts in topically related images

1. A method for extracting an object of interest out of each image in a group of digital images that contain the object of interest, comprising:

(a) providing a group of digital images, each containing the object of interest with a background;

(b) selecting a seed image from the group of digital images, and displaying the seed image to a user;

(c) the user providing at least one marking for the seed image, which corresponds to a subset of pixels in the seed image that indicates whether the set of pixels belongs to a part of object of interest or a part of the background;

(d) producing from the seed image and the marking a statistical model that can be used for separating the object of interest from the background in the group of images, wherein the statistical model includes:

(i) learned likelihood for a feature vector belonging to foreground and background; and

(ii) learned distances or affinities between features such that these distances reflect the input received via the user marking; and

(e) applying the statistical model to each image in the group of digital images to produce a cutout of the object of interest from each digital image.

2. The method of claim 1 , wherein step (a) further comprises:

(i) providing a collection of digital images with associated metadata;

(ii) analyzing either the metadata or image content or both to identify subsets of topically related digital images; and

(iii) producing the group of digital images from the subset of similar images.

3. The method of claim 2 , wherein:

(i) metadata includes information having date stamp, geotags, camera parameters (focal length), user notes or labels; and

(ii) image content is based on visual features including color features or texture features, or a combination of both.

4. The method of claim 1 , wherein the seed image is selected from the group of digital images by:

(i) randomly choosing an image out of the group; or

(ii) a heuristic that chooses the image with the most non-informative distribution of visual features among all images in the group.

5. The method of claim 1 , wherein:

(i) a marking includes a scribble, stroke, rectangle, or other designation of a subset of image pixels, some of which are marked as belonging to foreground, while others belonging to background; and

(ii) this marking is received via a user-interface on a display screen and via a user input devices.

6. The method of claim 1 further includes computing a plurality of cues, individually or in combination, including uncertainty-based, scribble-based, or global image cues, to indicate areas in the seed image where the user marking is helpful.

7. The method of claim 1 further includes using the object cutouts to produce an image product, including:

(i) producing a collage from the object cutouts in a group;

(ii) removing unwanted object and filling in the resulting blank space using texture synthesis or in-painting;

(iii) compositing one or more of the object cutouts on a new image background; or

(iv) producing samples of the object for training a detector for the object.