Shape recognition device, shape recognition program, and shape recognition method

• US 9,778,464 B2
• Filed: 07/23/2013
• Issued: 10/03/2017
• Est. Priority Date: 02/19/2013
• Status: Active Grant

• Current Assignee: Chikara Minami
• Original Assignee: Miramar Services Inc.
• Inventors: Lundberg, Johannes
• Primary Examiner(s): Park, Edward
• Assistant Examiner(s): Vanchy, Jr., Michael
• Application Number:
  US14/768,484
• Publication Number:
  US 20160004907A1
• Time in Patent Office: 1,533 Days
• CPC Class Codes: G02B 2027/0138 comprising image capture systems, e.g. camera
• CPC Class Codes: G02B 2027/014 comprising information/image processing systems
• CPC Class Codes: G02B 2027/0178 Eyeglass type eyeglass details G02C
• CPC Class Codes: G02B 27/017 Head mounted
• CPC Class Codes: G06F 3/011 Arrangements for interaction with the human body, e.g. for user immersion in virtual reality blind teaching G09B21/00
• 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
• CPC Class Codes: G06F 3/03 Arrangements for converting the position or the displacement of a member into a coded form
• CPC Class Codes: G06F 3/0304 Detection arrangements using opto-electronic means constructional details of pointing devices not related to the detection arrangement using opto-electronic means G06F3/033; optical digitisers G06F3/042
• CPC Class Codes: G06F 3/048 Interaction techniques based on graphical user interfaces [GUI]
• CPC Class Codes: G06F 3/0482 Interaction with lists of selectable items, e.g. menus
• CPC Class Codes: G06F 3/04842 Selection of displayed objects or displayed text elements G06F3/0482 takes precedence
• CPC Class Codes: G06F 3/04845 for image manipulation, e.g. dragging, rotation, expansion or change of colour
• CPC Class Codes: G06T 19/006 Mixed reality object pose determination, tracking or camera calibration for mixed reality G06T7/00
• CPC Class Codes: G06T 2200/04 involving 3D image data
• CPC Class Codes: G06T 2207/10004 Still image; Photographic image
• CPC Class Codes: G06T 2207/20228 Disparity calculation for image-based rendering
• CPC Class Codes: G06T 2207/30196 Human being; Person
• CPC Class Codes: G06T 2210/56 Particle system, point based geometry or rendering
• CPC Class Codes: G06T 7/20 Analysis of motion motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51
• CPC Class Codes: G06V 10/46 Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features colour feature extraction G06V10/56
• CPC Class Codes: G06V 40/107 : Static hand or arm
• CPC Class Codes: G06V 40/11 : Hand-related biometrics; Hand pose recognition
• CPC Class Codes: G06V 40/113 : Recognition of static hand signs
• CPC Class Codes: G06V 40/28 : Recognition of hand or arm movements, e.g. recognition of deaf sign language static hand signs G06V40/113
• CPC Class Codes: H04N 13/332 : Displays for viewing with the aid of special glasses or head-mounted displays [HMD]
• CPC Class Codes: H04N 13/395 : with depth sampling, i.e. the volume being constructed from a stack or sequence of 2D image planes

Abstract

Provided are a shape recognition device, a shape recognition program, and a shape recognition method capable of obtaining more accurate information for recognizing an outer shape of a target object. A shape recognition device according to the present invention includes: an outer shape detection unit that detects an outer shape of a hand; a reference point extraction unit that extracts a central point of a maximum inscribed circle of the detected outer shape as a reference point; a distance measurement unit that measures a distance between the reference point and each of a plurality of outer shape points on the outer shape; and a feature recognition unit that determines a feature part of the outer shape from the plurality of outer shape points on the basis of the distance.

Claims

1. A shape recognition device comprising:

an outer shape detection unit that detects an outer shape of a hand;

a reference point extraction unit that extracts a central point of a maximum inscribed circle of the detected outer shape as a reference point;

a distance measurement unit that measures a distance between the reference point and each of a plurality of outer shape points on the outer shape; and

a feature recognition unit that determines a feature part of the outer shape from the plurality of outer shape points on the basis of the distance,

wherein the plurality of outer shape points on the outer shape are set at predetermined intervals along the outer shape,

wherein the reference point extraction unit sets a defined chord of the maximum inscribed circle that passes through the reference point, and sets the plurality of outer shape points at a predetermined interval on the defined chord,

wherein the outer shape detection unit determines a point on a surface of the hand that corresponds to a depth level of a target point with respect to a palm of the hand, or the outer shape detection unit determines a point on a surface of the hand that corresponds to a depth level of a target point with respect to a finger of the hand, and

wherein the outer shape detection unit determines a palmar side of the hand or a dorsal side of the hand based on the depth level.

2. The shape recognition device according to claim 1, wherein the plurality of outer shape points on the outer shape are each obtained as an intersection point between a half line and the outer shape, the half line being drawn through a rotation for each predetermined angle about the reference point as a rotation center.

3. The shape recognition device according to claim 1, wherein the outer shape detection unit is a depth level sensor or an image sensor.

4. The shape recognition device according to claim 1, further comprising a display device capable of displaying a stereoscopic image, wherein

the outer shape detection unit includes a depth level sensor that measures a distance to the hand, and detects the outer shape of the hand in a common region in which a stereoscopic region of the stereoscopic image generated by the display device and a depth level detection region overlap with each other.

5. A head-mounted display device comprising the shape recognition device according to claim 1.

6. A processor encoded with a shape recognition program that when executed by the processor performs the following operations comprising:

an outer shape detection process of detecting an outer shape of a hand;

a reference point extraction process of extracting a central point of a maximum inscribed circle of the detected outer shape as a reference point;

a distance measurement process of measuring a distance between the reference point and each of a plurality of outer shape points on the outer shape; and

a feature recognition process of determining, using a processor, a feature part of the outer shape from the plurality of outer shape points on the basis of the distance,

wherein the plurality of outer shape points on the outer shape are set at predetermined intervals along the outer shape,

wherein the reference point extraction process sets a defined chord of the maximum inscribed circle that passes through the reference point, and sets the plurality of outer shape points at a predetermined interval on the defined chord,

wherein the outer shape detection process determines a point on a surface of the hand that corresponds to a depth level of a target point with respect to a palm of the hand, or the outer shape detection process determines a point on a surface of the hand that corresponds to a depth level of a target point with respect to a finger of the hand, and

wherein the outer shape detection process determines a palmar side of the hand or a dorsal side of the hand based on the depth level.

7. The processor encoded with a shape recognition program according to claim 6, wherein the plurality of outer shape points on the outer shape are each obtained as an intersection point between a half line and the outer shape, the half line being drawn through a rotation for each predetermined angle about the reference point as a rotation center.

8. A shape recognition method comprising:

an outer shape detection step of detecting an outer shape of a hand;

a reference point extraction step of extracting a central point of a maximum inscribed circle of the detected outer shape as a reference point;

a distance measurement step of measuring a distance between the reference point and each of a plurality of outer shape points on the outer shape; and

a feature recognition step of determining, using a processor, a feature part of the outer shape from the plurality of outer shape points on the basis of the distance,

wherein the plurality of outer shape points on the outer shape are set at predetermined intervals along the outer shape,

wherein the reference point extraction step sets a defined chord of the maximum inscribed circle that passes through the reference point, and sets the plurality of outer shape points at a predetermined interval on the defined chord,

wherein the outer shape detection step determines a point on a surface of the hand that corresponds to a depth level of a target point with respect to a palm of the hand, or the outer shape detection step determines a point on a surface of the hand that corresponds to a depth level of a target point with respect to a finger of the hand, and

wherein the outer shape detection step determines a palmar side of the hand or a dorsal side of the hand based on the depth level.

9. The shape recognition method according to claim 8, wherein the plurality of outer shape points on the outer shape are each obtained as an intersection point between a half line and the outer shape, the half line being drawn through a rotation for each predetermined angle about the reference point as a rotation center.