Integrating feature extraction via local sequential embedding for automatic handwriting recognition

1. A system for integrating features, comprising:

a processor configured to:

determine a value associated with a temporal feature for a point associated with a sequence of points;

determine a value associated with a spatial feature for the point, computed from a set of points including: the point, a first subset of points of the sequence preceding a sequence position associated with the point, and a second subset of points following the sequence position associated with the point;

include the value associated with the spatial feature and the value associated with the temporal feature in a single feature vector having both values; and

use at least the feature vector to decode for a character based at least in part on using one or more integrated recognition models configured to receive an input associated with at least a temporal feature and a spatial feature; and

a memory coupled to the processor and configured to provide the processor with instructions.

2. The system of claim 1 , wherein the point comprises a sample point included in the sequence of points, and the sequence of points is derived from a handwriting input.

3. The system of claim 1 , wherein the point comprises a pixel.

4. The system of claim 1 , wherein the point is associated with a (x,y) coordinate.

5. The system of claim 1 , wherein the value associated with the temporal feature is associated with at least a temporal or spatial neighborhood of points associated with the point.

6. The system of claim 1 , wherein the one or more integrated recognition models are trained on an integration of spatial information and temporal information.

7. The system of claim 1 , wherein the spatial feature may include one or more of the following: chain or stroke code, sector occupancy, and pixel-level Rutovitz crossing number.

8. The system of claim 1 , wherein the temporal feature may include one or more of the following: position, velocity, and acceleration.

9. A method for integrating features, comprising:

at an electronic device having a processor and memory:

determining a value associated with a temporal feature for a point associated with a sequence of points;

determining a value associated with a spatial feature for the point, computed from a set of points including: the point, a first subset of points of the sequence preceding a sequence position associated with the point, and a second subset of points following the sequence position associated with the point;

including the value associated with the spatial feature and the value associated with the temporal feature in a single feature vector having both values; and

using at least the feature vector to decode for a character based at least in part on using one or more integrated recognition models configured to receive an input associated with at least a temporal feature and a spatial feature.

10. The method of claim 9 , wherein the point comprises a sample point included in the sequence of points, and the sequence of points is derived from a handwriting input.

11. The method of claim 9 , wherein the value associated with the temporal feature is associated with at least a temporal or spatial neighborhood of points associated with the point.

12. The method of claim 9 , wherein the one or more integrated recognition models are trained on an integration of spatial information and temporal information.

13. A computer program product for integrating features, the computer program product being embodied in a non-transitory computer readable medium and comprising computer instructions for:

determining a value associated with a temporal feature for a point associated with a sequence of points;

determining a value associated with a spatial feature for the point, computed from a set of points including: the point, a first subset of points of the sequence preceding a sequence position associated with the point, and a second subset of points following the sequence position associated with the point;

including the value associated with the spatial feature and the value associated with the temporal feature in a single feature vector having both values; and

using at least the feature vector to decode for a character based at least in part on using one or more integrated recognition models configured to receive an input associated with at least a temporal feature and a spatial feature.

14. A system of determining a transform, comprising:

a processor configured to:

determine, for a point associated with a sequence of points, a set of points including:

the point, a first subset of points of the sequence preceding a sequence position associated with the point, and a second subset of points following the sequence position associated with the point;

determine the transform associated with the point based at least in part on the set of points;

include a value determined from the transform in a single feature vector including values corresponding to one or more of a spatial feature and a temporal feature associated with the point; and

use the feature vector to decode for a character using an integrated recognition model; and

a memory coupled to the processor and configured to provide the processor with instructions.

15. The system of claim 14 , wherein the transform comprises a 1-dimensional discrete cosine transform.

16. The system of claim 14 , wherein the transform comprises a Haar wavelets-based transform.

17. The system of claim 14 , wherein the transform comprises a Fourier descriptor-based transform.

18. The system of claim 14 , wherein the first subset of points comprises a same number of points as the second subset of points.

19. The system of claim 14 , wherein the set of points is included within a sliding window associated with a size comprising a number of points present within the set of points.

20. The system of claim 14 , wherein the point comprises a pixel.

21. A method of determining a transform, comprising:

at an electronic device having a processor and memory:

determining, for a point associated with a sequence of points, a set of points including: the point, a first subset of points of the sequence preceding a sequence position associated with the point, and a second subset of points following the sequence position associated with the point;

determining the transform associated with the point based at least in part on the set of points;

including a value determined from the transform in a single feature vector including values corresponding to one or more of a spatial feature and a temporal feature associated with the point; and

using the feature vector to decode for a character using an integrated recognition model.

22. The method of claim 21 , wherein the first subset of points comprises a same number of points as the second subset of points.

23. The method of claim 21 , wherein the set of points is included within a sliding window associated with a size comprising a number of points present within the set of points.

24. A computer program product for determining a transform, the computer program product being embodied in a non-transitory computer readable medium and comprising computer instructions for:

determining, for a point associated with a sequence of points, a set of points including: the point, a first subset of points of the sequence preceding a sequence position associated with the point, and a second subset of points following the sequence position associated with the point;

determining the transform associated with the point based at least in part on the set of points;

including a value determined from the transform in a single feature vector including values corresponding to one or more of a spatial feature and a temporal feature associated with the point; and

using the feature vector to decode for a character using an integrated recognition model.