Object tracking
First Claim
1. A digital video encoder, comprising:
- a segmentation module configured to segment frames in a digital video sequence into background regions and object regions; and
an object parameter generator configured to generate object motion and object appearance parameters based on segmented object regions, the object parameter generator including a tracking module configured to track object motion and changes in object appearance of segmented object regions, the tracking object motion including;
identifying object motion parameter states based on particle filtering; and
tracking one or more object regions based on one or more object motion parameter states selected from the identified object motion parameter states,wherein the tracking module is configured to;
estimate a target state by selecting one of the identified motion parameter states;
determine a similarity of a normalized color histogram for a region associated with the estimated target state and an initial color histogram for a region associated with an object;
compare the similarity to a first similarity threshold;
when the similarity exceeds the first similarity threshold, set a target state for the region associated with the object to the estimated target state;
when the similarity does not exceed the first similarity threshold, selectively, identify new motion parameter states; and
estimate a new target state by selecting one of the identified new motion parameter states; and
when the similarity does not exceed the first similarity threshold and a number of iterations of identifying new motion parameter states exceeds an iteration threshold;
determine whether the object is visible based on a comparison of the similarity to a second similarity threshold and a comparison of a reconstruction error associated with the estimated target state to a reconstruction error threshold; and
when it is determined that the object is visible, setting the target state for the region associated with the object to an identified state having a lowest reconstruction error.
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Abstract
A video compression framework based on parametric object and background compression is proposed. At the encoder, an object is detected and frames are segmented into regions corresponding to the foreground object and the background. The encoder generates object motion and appearance parameters. The motion or warping parameters may include at least two parameters for object translation; two parameters for object scaling in two primary axes and one object orientation parameter indicating a rotation of the object. Particle filtering may be employed to generate the object motion parameters. The proposed methodology is the formalization of the concept and usability for perceptual quality scalability layer for Region(s) of Interest. A coded video sequence format is proposed which aims at “network friendly” video representation supporting appearance and generalized motion of object(s).
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Citations
19 Claims
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1. A digital video encoder, comprising:
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a segmentation module configured to segment frames in a digital video sequence into background regions and object regions; and an object parameter generator configured to generate object motion and object appearance parameters based on segmented object regions, the object parameter generator including a tracking module configured to track object motion and changes in object appearance of segmented object regions, the tracking object motion including; identifying object motion parameter states based on particle filtering; and tracking one or more object regions based on one or more object motion parameter states selected from the identified object motion parameter states, wherein the tracking module is configured to; estimate a target state by selecting one of the identified motion parameter states; determine a similarity of a normalized color histogram for a region associated with the estimated target state and an initial color histogram for a region associated with an object; compare the similarity to a first similarity threshold; when the similarity exceeds the first similarity threshold, set a target state for the region associated with the object to the estimated target state; when the similarity does not exceed the first similarity threshold, selectively, identify new motion parameter states; and estimate a new target state by selecting one of the identified new motion parameter states; and when the similarity does not exceed the first similarity threshold and a number of iterations of identifying new motion parameter states exceeds an iteration threshold; determine whether the object is visible based on a comparison of the similarity to a second similarity threshold and a comparison of a reconstruction error associated with the estimated target state to a reconstruction error threshold; and when it is determined that the object is visible, setting the target state for the region associated with the object to an identified state having a lowest reconstruction error. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A method, comprising:
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segmenting frames in a digital video sequence into background regions and object regions; generating object motion parameters of a plurality of segmented object regions based on particle filtering; generating object appearance parameters of the plurality of segmented object regions, the generating object appearance parameters including tracking changes in appearance of one or more of the plurality of segmented object regions; and encoding the object motion parameters and the object appearance parameters in a bit stream, wherein the generating object motion parameters comprises selecting one of the identified motion parameter states as an estimated target state, and the method comprises; determining a similarity of a normalized color histogram for a region associated with the estimated target state and an initial color histogram for the segmented object region; comparing the similarity to a first similarity threshold; when the similarity exceeds the first similarity threshold, setting a target state for the region associated with the object to the estimated target state; and when the similarity does not exceed the first similarity threshold, selectively, identifying new motion parameter states; and estimating a new target state by selecting one of the identified new motion parameter states; and when the similarity does not exceed the first similarity threshold and a number of iterations of identifying new motion parameter states exceeds an iteration threshold, the method comprises; determining whether the object is visible based on a comparison of the similarity to a second similarity threshold and a comparison of a reconstruction error associated with the estimated target state to a reconstruction error threshold; and when it is determined that the object is visible, setting the target state for the region associated with the object to an identified state having a lowest reconstruction error. - View Dependent Claims (10, 11, 12, 13, 14, 15)
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16. A non-transitory computer-readable medium whose contents cause an encoder to perform a method of encoding a video image sequence, the method comprising:
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segmenting frames in a digital video sequence into background regions and object regions; generating object motion parameters of a plurality of segmented object regions based on particle filtering; generating object appearance parameters of the plurality of segmented object regions, the generating object appearance parameters including tracking changes in appearance of one or more of the plurality of segmented object regions; and encoding the object motion parameters and the object appearance parameters in a bit stream, wherein the generating object motion parameters comprises selecting one of the identified motion parameter states as an estimated target state, and the method comprises; determining a similarity of a normalized color histogram for a region associated with the estimated target state and an initial color histogram for the segmented object region; comparing the similarity to a first similarity threshold; when the similarity exceeds the first similarity threshold, setting a target state for the region associated with the object to the estimated target state; and when the similarity does not exceed the first similarity threshold, selectively, identifying new motion parameter states; and estimating a new target state by selecting one of the identified new motion parameter states; and when the similarity does not exceed the first similarity threshold and a number of iterations of identifying new motion parameter states exceeds an iteration threshold, the method comprises; determining whether the object is visible based on a comparison of the similarity to a second similarity threshold and a comparison of a reconstruction error associated with the estimated target state to a reconstruction error threshold; and when it is determined that the object is visible, setting the target state for the region associated with the object to an identified state having a lowest reconstruction error. - View Dependent Claims (17, 18, 19)
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Specification