Apparatus and method for processing video data

A computer-implemented method of generating an encoded form of video signal data from a plurality of video frames, the method comprising:

• detecting at least one object in the two or more video frames;
• tracking the at least one object through the two or more frames of the video frames;
• segmenting the pel data associated with the at least one object from other pel data in the two or more video frames so as to generate a second intermediate form of the data, the segmenting utilizing a spatial segmentation of the pel data;
• and
• identifying corresponding elements of at least one object in two or more of the video frames;
• analyzing the corresponding elements to generate relationships between the corresponding elements;
• generating correspondence models by using the relationships between the corresponding elements;
• integrating the relationships between the corresponding elements into a model of global motion;
• and
• re-sampling pel data associated with the at least one object in the two or more video frames by utilizing the correspondence models, thereby generating re-sampled pel data, the re-sampled pel data representing a first intermediate form of the data;
• and
• restoring the spatial positions of the re-sampled pel data by utilizing the correspondence models, thereby generating restored pels;
• and
• recombining the restored pels together with an associated portion of the second intermediate form of the data to create an original video frame;
• and
• wherein no detection would indicate an indirect detection for the whole frame;
• and
• wherein the detecting and tracking comprise using a face detection algorithm;
• and
• wherein generating correspondence models comprises using a robust estimator for the solution of a multi-dimensional projective motion model, and wherein analyzing the corresponding elements comprises using an appearance-based motion estimation between two or more of the video frames.

A computer-implemented method of separating data vectors residing in discrete linear subspaces, the method comprising:

• (a) performing subspace segmentation on a set of the data vectors;
• and
• (b) constraining subspace segmentation criteria through application of a tangent vector analysis in an implicit vector space;
• wherein performing subspace segmentation comprises using GPCA;
• wherein the implicit vector space comprises the Veronese Map;
• and wherein the tangent vector analysis comprises the Legendre Transform.