Tracking semantic objects in vector image sequences

A computer system for tracking semantic objects in a vector image sequence of image frames, the system comprising:

• a spatial segmentation module for segmenting a current image frame in the vector image sequence into plural regions, each of the plural regions comprising image points having image values that satisfy a homogeneity criterion;
• a motion estimator module for estimating the motion between each of the plural regions in the current image frame and a reference image frame, and for determining a motion parameter for each of the plural regions that approximates the motion of the region between the current image frame and the reference image frame, wherein the reference image frame includes a semantic object for which a semantic object boundary was previously computed;
• and
• a region classifier module for applying the motion parameter of each of the plural regions to the region to compute a predicted region in the reference image frame, and for classifying each of the plural regions as being part of or not being part of the semantic object depending on the extent to which the predicted region for the region falls within the previously computed semantic object boundary in the reference image frame;
• wherein a corresponding semantic object boundary in the current image frame is formed from each region classified as being part of the semantic object.

A method for tracking semantic objects in vector image sequences, the method comprising:

• performing spatial segmentation on a current image frame to identify plural regions of discrete image points with homogenous image values;
• performing motion estimation between each of the plural regions in the current image frame and a target image frame in which a boundary of a semantic object is known;
• using the motion estimation for each of the plural regions to warp the image points in the region to locations in the target image frame;
• for each region of the plural regions, when at least a threshold amount of the warped image points for the region overlap the semantic object with the known boundary in the target image frame, classifying the region as originating from the semantic object;
• and
• forming a boundary of the semantic object in the current image frame based upon each of the plural regions in the current image frame that are classified as originating from the semantic object.

A method for tracking semantic objects in vector image sequences, the method comprising:

• performing spatial segmentation on a current image frame to identify plural regions of discrete image points with homogenous image values, where each of the plural regions comprises image points, and where each of the plural regions is determined to be homogenous by only adding neighboring image points to the region where the difference between a maximum image value and a minimum image value in the region after adding each neighboring image point is below a threshold;
• performing region-based motion estimation between each of the plural regions in the current image frame and an immediate previous image frame in the vector image sequence in which a boundary of a semantic object is known;
• using the motion estimated for each of the plural regions to warp the image points in the region to locations in the immediate previous image frame;
• for each of the plural regions, when at least a threshold amount of the warped image points for the region overlap the semantic object with the known boundary in the immediate previous image frame, classifying the region as originating from the semantic object;
• and
• forming a boundary for the semantic object in the current image frame based upon which of the plural regions in the current image frame are classified as originating from the semantic object.

A method of tracking an object in a vector image sequence using backward region-based classification, the method comprising:

• computing a boundary of an object in a first image frame of a vector image sequence;
• segmenting a second image frame of the vector image sequence into plural regions;
• based upon motion estimates, warping each of the plural regions backward into the first image frame;
• for each of the plural regions of the second image frame, if a threshold portion of the warped region lies within the previously computed boundary in the first image frame, classifying the region of the second image frame as part of the object.

A computer-readable medium having instructions stored thereon for causing a computer system programmed thereby to perform a method of tracking an object in a vector image sequence using backward region-based classification, the method comprising:

• computing a boundary of an object in a previous image frame of a vector image sequence;
• segmenting a current image frame of a vector image sequence into plural regions;
• based upon motion estimates for the plural regions of the current image frame, warping each of the plural regions backward into the previous image frame;
• for each of the plural regions of the current image frame, if a threshold portion of the warped region lies within the previously computed boundary of the object in the previous image frame, classifying the region of the current image frame as part of the object.

A method of tracking an object in a vector image sequence using backward region-based classification, the method comprising:

• computing a boundary of an object in a first image frame of a vector image sequence;
• segmenting a second image frame of the vector image sequence into plural regions;
• for each of the plural regions of the second image frame,
• associating the region with a corresponding region of the first image frame based upon motion estimation from the second image frame back to the first image frame;
• and
• if a threshold portion of the associated corresponding region of the first image frame lies within the previously computed boundary in the first image frame, classifying the region of the second image frame as part of the object.