TW201128463A - Hand trajectory recognition system and method thereof - Google Patents

Abstract

A hand trajectory recognition system and method thereof are disclosed, wherein the system comprises a video camera module, a moving object detection module, a finger detection module, a feature extraction module and a trajectory recognition module. The video camera module captures a hand motion image. The moving object detection module integrates background reconstruction and foreground object color analysis technologies to find out a hand in a motion. The finger detection module positions a finger tip according to a separated hand image, and records a trajectory according to the movement of the finger tip. The feature extraction module utilizes a chain code as a trajectory feature. The trajectory recognition module utilizes radical basis function neural networks (RBFNN) to classify the chain code feature, and performs correction by means of a confusing set to generate hand trajectory data, which can be used as a basis of a computer action so as to improve the convenience of human-machine communications, thereby facilitating computer control or character input.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a hand trajectory recognition system and method thereof, and more particularly to having a hand video interface and using a chain code as a trace feature to re-use a confusing set for correction. [Prior Art] Currently applied to handwriting technology, the conventional technology requires additional input devices, such as a tablet, a touch panel, and the like is a mussel, which increases the cost of related products. In addition, in the past, most of these technologies were needed—only special (four) pens were used as input aids, and most of these pens were light and short, easy to lose, and caused a lot of inconvenience in operation. Nowadays, the face control technology is already available. (4) Handwriting, however, these touches face, there are problems of thick thickness, easy rain, and poor penetration. Although the touch panel has gradually become popular in multi-type mobile phones, automatic cross-border machines, and some touch-sensitive, one-five computers, the target of the touch panel is not realistic, so the type of sophomore touch is high. Direct popularization, such as TV, is stupid: the city's second two, the touch interface operation of large panel applications: for the user needs to go back and forth between the seat and the panel to do similar - hand hand identification system and its method, the use of points. The remote operation of the touch interface to solve the lack of the above-mentioned system technology 201128463 t

[Summary of the Invention] The main purpose of the joint is to provide a hand-existing identification system and a camera module, a moving object detection module, a finger=,,,,,, and a ship's take-up and touch display. , Everything, axis object gamma "final background background heavy object color analysis technology to find out the hand module in action according to the separated hand scene 彡 silly m end fine, finger tip, and according to the tip of the finger Execution, the characteristic couch modulo, the group uses the chain code as the trajectory touch radial base function class _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Therefore, the present invention utilizes video signal detection to implement handwriting input, and can be used as a basis for computer actions, performing computer control or text input, thereby improving the convenience of human-machine communication, and can be applied to computer home appliances, instant脑 Brain teaching, office meetings, data entry, article writing or drawing gives the human-machine interface Φ 'especially for patients with language disorders, without any external input device' Refers to the way of writing to talk and communicate. [Embodiment] Hereinafter, embodiments of the present invention will be described in more detail with reference to the drawings and the component symbols, so that the skilled person can implement the book after studying the book. Referring to the first figure, a schematic diagram of the hand trace recognition system of the present invention. As shown in the first figure, the hand track recognition system of the present invention comprises a video camera module 10, a moving object detecting module 20, a finger detecting module 30, a feature 201128463 capturing module 40 and a track recognition module. 50, used to provide a hand video interface for track recognition. Depending on the 5fl camera> machine module 1 〇 capture picture to generate a plurality of continuous motion picture data T1, and the video camera module 1 〇 may include a charge coupled device (CCD) or a complementary MOS half (CM〇s) a camera with a plurality of pixels. Each motion picture data T1 includes a plurality of pixel values, and each pixel has a corresponding pixel value. The animal detecting module 20 receives the moving image data T1 to create a back image, and creates a decorative object T2 of the secret image data T1. As the image moves and the time changes, the pixel values will also change synchronously. Therefore, the pixel value of the moving image data T1 is firstly integrated to establish a histogram p St〇gram) 'Reuse kernel function density estimation method (Kernel) Density (for duty) is the corresponding pixel for each pixel. The probability is based on the next moving image data Τ1 and each image (4) is the non-moving object T2, and the judging a Mobile

The probability is small, the required == probability is large, the background is distributed, the hand is detected, the pull group 30 receives the moving object Τ2, first finds the fingertip, and also uses the color analysis technology to filter the moving object Τ2 The image of the part 32 _, ^ 6 second g household; -, then, two, at the same time the knife leaves = 32 overlapping intersection 33,%, 35 as the center, a: ^ moment = refers to (10), round _ Paste her == 201128463 τ3, touch the transcript to touch the fingertips Τ 4 Li Jin W in the "writing feature couch, and generate trajectory features ^ sign ^ Dan extraction based on writing characteristics, such as strokes have a turn, pen bite

Iff _ sharp _ speed will slow down, and from the fingertip trajectory Τ 3 曰曰 ', the degree of silk transfer to take the ridged point f tip rail shot 3 towel private «, the riding 昼 and the writing pen Γ knife Leave the pen and keep only the book _ for judgment. ^ 昼 According to the direction of writing, fh fine Code) coded the ruler as a positive integer, and use the histogram to calculate the probability of the direction of the trajectory of the Kui write ^, and then use the kernel function density to estimate the probability distribution. Due to the cyclic coding characteristics of the chain code, the range of functions estimated by the ^^ estimation method will fall below 〇 or exceed =, the _ direction is _region·, and the corresponding probability must be $plus = 〇 'This is called the cyclic chain probability distribution estimation, and the estimated probability function is taken as the touch (four) trajectory feature T4. The trajectory level 50 receives the trajectory feature T4 for trajectory identification, and the second writing symbol Τ5' is first classified according to the radial basal function Neural Neural Network (RBFNN) to the orbit η τ Α π to generate Preliminary results. & different text or symbols in the track feature ^ will have a similar chain code distribution, such as 〇 and 0 ' 2 and Z ' and therefore 混 攸 (10) using (four) to repair = knife step classification results 'and produce the required writing symbols T5, which can include handwritten symbols or handwritten words, can be used as a turn of the electric lining, thereby enabling computer control or text input. Referring to the third figure, a schematic diagram of the method for identifying the hand trajectory of the present invention. Such as .201128463 S1° ^ Generates a continuous plurality of motion pictures: The camera module captures the picture, including = pixel values, and each pixel value corresponds to - image; Becco and other motion picture data, and! The animal piece gamma|J module receives the large rate of distribution like 辛t背旦=approximate distribution probability, and distributes the machine to the machine, and distributes the dog, body', to the desired moving object, and enters Step coffee-finger squadron group receives the turn] Μ Non-hand moving object and then two: = surgery part, and then encloses the rectangle of the hand image framed around the intersection of the rectangles: σ ” The intersection with the smallest angle "points of continuous position is honoured by the age of the staff. "In the next step, in step S40, using a feature to trace, the first step is to use the fingertip to move the catch. The estimated pause is to stop the point and stop the point to divide the difficulty of the T3 towel. Gan + do - leave the pen and book (^Γη Code) ^: N;; ^ ^ ^ the probability of the direction of the trajectory of the movement to statistics, and then write strokes to estimate the cloth, and the estimated probability is recorded as the track = estimate The test finally proceeds to step S50, using a 舳 feature 'first based on the radial basis function classpath; obstruction: r:=, then _set==, ,, and, and produce the desired written symbol. Negative 201128463 The video camera module and the moving object of the above-mentioned method of the present day and the moon are: the temple levy module and the trajectory identification module system 20 Feng ^ video frequency to do. Move the secret detection module rent feature Na module 40 The gamma identification module is characterized in that the invention is not limited by the input device.

Another feature of the finger as the input interface I:= is that for the hand recognition technology, the f-tip can be positioned with the smallest angle of the hand of the wheel to locate the position: =Γ:ΓΓ to locate the fingertip, The probability distribution is used as the detour feature, and the radial path is used for classification, and the output result is transparently set to "to correct it to achieve a better recognition rate.摔作戍文(4) Hand trajectory identification system can control the computer =====convenience' can be applied to Wentong Touche I, office (four) meeting, data input, gift s, no need to test obstacles Through any external input device, you can directly use the way of handwriting to communicate and communicate. The present invention is intended to be merely a preferred embodiment for explaining the present invention, and it is not intended to be a simplification of the invention, and it is intended to be included in the scope of the present invention. 201128463 [Simple description of the diagram] The first figure is a schematic diagram of the hand recognition identification system of the present invention. The second figure is a schematic diagram of finger detection according to the present invention. The second figure is a schematic diagram of the method for identifying the hand trajectory of the present invention. [Main component symbol description] 10 video camera module 20 mobile object detection module 30 finger debt measurement module 31 hand 32 enclosing rectangle 33 intersection 34 intersection 35 intersection 40 feature capture module 50 track recognition module

The S10 uses the video camera module to generate a dynamic image data by taking a picture. The S20 uses the moving object detection module to receive the dynamic image number density estimation method. The mobile object and the wrong core S30 use the finger_module to receive the moving object. The minimum refresh angle intersection is formed to form the fingertip representation S40, and the feature extraction module is used to receive the fingerprint track for pen extraction and writing feature extraction to generate the trajectory feature S50. The trajectory identification module is used to receive the trajectory feature for performing the recognition identification. Generated writing symbols 201128463 T1 dynamic image data Ding 2 moving objects Τ 3 fingertips Τ 4 track features Τ 5 writing symbols

Claims (1)

201128463 VII. Patent application scope: 1. A hand trajectory identification system, comprising: a video camera module for taking a picture to generate a continuous plurality of dynamic image poor materials. Each of the dynamic image data includes a plurality of pixels. Value, and each pixel value corresponds to one pixel; a moving object side module receives the moving image data, and uses the histogram to count the pixel values, and then subtracts the digital side method Density Estimation, _ Each pixel distributes a solution by generating an approximation corresponding pixel value, and whether the pixel touches the pixel is a non-moving-background or moving-moving object; The hand-cranked Russian-speaking group "receives the moving object, first finds the fingertip, that is, the hand-cranked end" is using the color analysis technique to pass the non-hand moving object in the moving object, and enters the action towel. The hand, at the same time, separates the hand, and then frames the image of the hand with the encircling rectangle, and the intersection of the hand and the surrounding rectangle is centered to calculate ^ = the angle of the reading contour segment, and the intersection with the smallest corner loss is the 4-point position. Finally, the position of the fingertip is touched by the shape-point trajectory 'private representative-writing pen recording; the first is based on a writing feature and 彳The purpose of the line is to extract the fish gold to write the feature record 'Calling the trajectory characteristics' and delete the entry 苇昼, leave the pen and write strokes. 201128463 Enter the pen 昼 and _ strokes, the Jianliu writing pen knows the supply, and the The column breaks the first line to write the amount of material __ code (Chain _ code, "positive integer, and the probability of moving the direction of the execution of the straight square pen writing book, the re-function function density estimation method to estimate the probability Distribution to produce a corresponding probability function, as a post Characterized by executing a track identification; and A trace identification, receiving trace features, performing - trace identification, to produce - book (four) 'silk to the base of the neural network aris Function Neural Networks, RBFm) Mm hoof reading, shouting "m _ The side uses the suffix set s (C〇nfusing Set) to correct the written symbols of the preliminary classification result. The hand-tracking system described in the item, wherein the electrical component (GCD) or the complementary gold oxide 2. According to the scope of the patent application, the video camera module comprises a half (CMOS) camera. The moving object detection The judgment criterion of the module is that, according to the next chest image, the pixel with a large probability of distribution belongs to the background, and the pixel with the small side rate belongs to the moving object. The hand trajectory identification system, in which two '. butterfly shift f, pen or pen movement when the fingertip moves 201128463 5 · - hand trajectory identification method, including: camera module to capture the face, produce continuous The plurality of moving images are like a poor material 'each—the dynamic image data includes a plurality of pixel values, and each pixel value corresponds to one pixel; the animal piece uses the mobile object detection mode to receive the dynamic image data, The graph performs the singularity of the nucleus, the ____ each pixel to generate an approximation corresponding pixel value distribution probability, and uses a judgment criterion to determine whether the pixel is untouched _-background or mobile utilization - Finger detection The module receives the moving object 'first find the fingertip, that is, the big end of the palm of the hand' is the color analysis technical surface, the moving object of the non-hand in the middle part, and then finds the hand in the action, and simultaneously separates An image of the oblique portion, and then the rim of the image of the hand is framed by the enclosing rectangle. The third point is centered on an intersection point where the hand overlaps the enclosing rectangle to calculate the rim line segment after the intersection point. An angle, the intersection with the smallest angle is the position of the fingertip, and finally connected to the continuous position of the fingertip to form - fingertips, thereby representing - writing strokes; using - feature training module receiving The fingertips are obscured, and the strokes are drawn and written, and the characteristics of the strokes are written, the domain is firstly based on the movement speed of the fingertips to extract the pause point, and then the stop is used; the point is used to distinguish the fingertip trajectory. Entering the pen, leaving the pen and writing strokes, and deleting the pen and leaving the pen, leaving only the writing pen for judgment, and the LSI 13 '201128463 judges that the pen is first in the N direction according to the writing direction. Key code N is a positive integer, and the probability of writing the direction of the trajectory of the writing stroke is counted by the histogram. The kernel function density is estimated to estimate the probability distribution to generate a corresponding probability function, which is used as a signature for subsequent identification. And using the trajectory identification module to receive the characterization feature, performing a trace identification, = raw-writing symbol, 鲥 驰 基底 基底 基底 基底 基底 基底 基底 基底 轨迹 轨迹 轨迹 轨迹 轨迹 轨迹 轨迹 轨迹 轨迹 轨迹 轨迹 轨迹 轨迹 轨迹Reuse the confusion set to correct the _ step age, and produce the hand track described in item 5 of the patent scope;: symbol; . According to Shen 4 Na _5 tearing hand (4) the benchmark of the moving object detection module Yes, according to the image data, the pixel with a large probability of distribution belongs to the moving object. In the distribution machine 8. = patent application · Hand rail according to item 5: Writing features include pen _, pen or pen speed will slow down. Fingertip movement during movement