APPARATUS AND METHOD FOR PROCESSING USER INPUT USING MOTION OF OBJECT

• US 20140354537A1
• Filed: 05/22/2014
• Published: 12/04/2014
• Est. Priority Date: 05/29/2013
• Status: Active Grant

• Current Assignee: Samsung Electronics Co. Ltd.
• Original Assignee: Samsung Electronics Co. Ltd.
• Inventors: PARK, Keun Joo, LEE, Jun Haeng, RYU, Hyun Surk, KIM, Jun Seok, SHIN, Chang-Woo, WOO, Jooyeon, LEE, Kyoobin
• Granted Patent: US 9,696,812 B2
• Time in Patent Office: Days
• US Class Current: 345/156
• CPC Class Codes: G06F 3/017 Gesture based interaction, e.g. based on a set of recognized hand gestures interaction based on gestures traced on a digitiser G06F3/04883

Abstract

A user input processing apparatus using a motion of an object to determine whether to track the motion of the object, and track the motion of the object using an input image including information associated with the motion of the object.

Claims

1. An apparatus for processing a user input, the apparatus comprising:

a determiner configured to determine that at least one point corresponds to a first mode input instructing the apparatus to track motion of an object, based on an input image comprising the at least one point generated by sensing the motion of the object; and

a processor configured to track the motion of the object, in response to the determiner determining that the at least one point corresponds to the first mode input.

2. The apparatus of claim 1, further comprising:

a dynamic vision sensor configured to sense the motion of the object and output the input image based on the motion of the object.

3. The apparatus of claim 1, wherein the determiner is configured to determine that the at least one point corresponds to the first mode input by comparing a scattering of the at least one point to a threshold value and determine that the at least one point corresponds to the first mode input based on a result of the comparison.

4. The apparatus of claim 3, wherein the determiner is further configured to determine that the at least one point corresponds to a second mode input by comparing the scattering of the at least one point to the threshold value and determine that the at least one point corresponds to the second mode input based on a result of the comparison.

5. The apparatus of claim 3, wherein the determiner comprises:

a scattering calculator configured to calculate the scattering of the at least one point scattered in a predetermined direction.

6. The apparatus of claim 1, wherein the processor comprises:

a centroid calculator configured to calculate a centroid of the at least one point;

a line detector configured to detect a dominant line associated with the at least one point; and

a detector configured to detect a portion of the object based on the centroid and the dominant line.

7. The apparatus of claim 6, wherein the line detector comprises:

a transformer configured to obtain a plurality of lines by performing a Hough transformation on the at least one point; and

a line obtainer configured to obtain the dominant line based on the plurality of lines.

8. The apparatus of claim 6, wherein the detector comprises:

a projector configured to project the centroid onto the dominant line; and

an explorer configured to explore the dominant line from the projected location toward the portion of the object positioned in a predetermined direction.

9. The apparatus of claim 1, wherein the processor is configured to calculate an orientation vector of the at least one point, divide the at least one point into a predetermined number of sections, calculate feature vectors of the sections based on the orientation vector, and recognize a portion of the object based on the feature vectors.

10. The apparatus of claim 9, wherein a direction of the orientation vector is quantized to be one of a predetermined number of quantization directions.

11. The apparatus of claim 9, wherein the processor is configured to obtain a section corresponding to the portion of the object from among the predetermined number of sections by inputting a previously learned parameter and the feature vectors to a classifier.

12. The apparatus of claim 1, wherein the determiner is further configured to determine a pattern of the at least one point corresponds to a predetermined pose instructing suspension of the tracking.

13. The apparatus of claim 12, wherein the determiner comprises:

a centroid calculator configured to calculate a centroid of the at least one point;

a pattern detector configured to detect, among the at least one point, an area pattern of a point included in an area, separate from the centroid by at least a predetermined distance, in a predetermined direction; and

a verifier configured to determine whether the area pattern corresponds to the predetermined pose.

14. The apparatus of claim 12, wherein the determiner comprises:

a line filtering unit configured to extract a component of a predetermined direction by applying a line filter method to the at least one point;

a pattern detector configured to detect a component pattern of the at least one point based on the component of the predetermined direction; and

a verifier configured to determine whether the component pattern corresponds to the predetermined pose.

15. A method of processing a user input, the method comprising:

obtaining an event signal indicating movement of an object;

calculating a centroid of a plurality of pixels included in the event signal;

extracting a dominant line included of the plurality of pixels; and

recognizing a portion of the object based on the centroid and the dominant line.

16. The method of claim 15, wherein the obtaining comprises:

classifying the plurality of pixels into a plurality of blocks;

selecting blocks including at least a predetermined number of pixels from among the plurality of blocks; and

obtaining pixels included in the selected blocks.

17. The method of claim 15, further comprising:

calculating a scattering of the plurality of pixels included in the event signal;

comparing the scattering to a threshold value; and

switching an operation mode to a selection input processing mode based on a result of the comparing.

18. The method of claim 15, further comprising:

determining whether a pattern of the plurality of pixels corresponds to a predetermined pose indicating suspension of a tracking mode; and

switching an operation mode to a suspension mode based on a result of the determining.

28. A non-transitory computer-readable medium comprising a program which, when executed, causes a computer to perform the method of claim 15.

19. A user input processing method comprising:

obtaining an event signal in which a motion of an object is sensed;

dividing a plurality of pixels included in the event signal into a predetermined number of sections;

calculating orientation vectors of the plurality of pixels;

calculating feature vectors of the sections based on the orientation vectors; and

recognizing a portion of the object based on the feature vectors.

20. The method of claim 19, wherein the calculating of the orientation vectors comprises quantizing directions of the orientation vectors to be one of a predetermined number of quantization directions.

21. The method of claim 19, wherein the calculating of the feature vectors comprises calculating a vector sum of the orientation vectors of the pixels included in each of the sections, and generating a feature vector of each of the sections based on the vector sum.

22. The method of claim 19, wherein when the directions of the orientation vectors are quantized to be one of the predetermined number of quantization directions, the calculating of the feature vectors comprises:

counting a number of pixels corresponding to the quantization directions among the pixels included in each of the sections; and

generating a feature vector of each of the sections based on the number of pixels counted.

23. The method of claim 19, wherein the feature vector for each of the sections comprises elements corresponding to the quantization directions, and each of the elements is generated based on the number of pixels counted correspondingly to each of the quantization directions.

24. The method of claim 19, wherein the feature vector of each of the sections is generated based on an orientation vector corresponding to a quantization direction of which a number of pixels is the greatest among the quantization directions.

25. The method of claim 19, wherein the calculating of the feature vectors comprises:

extracting the most dominant vector from among the orientation vectors of the pixels in each of the sections; and

generating a feature vector for each of the sections based on the most dominant vector.

26. The method of claim 19, wherein the recognizing comprises acquiring a section corresponding to the portion of the object among the predetermined number of sections by inputting a learned parameter and the feature vectors to a classifier.

27. The method of claim 19, wherein the learned parameter is previously learned based on feature vectors of a plurality of training images and sections corresponding to the portion of the object in the plurality of training images.

29. A non-transitory computer-readable medium comprising a program which, when executed, causes a computer to perform the method of claim 19.