KR20180096378A - Method and apparatus for monitoring quality of sign language broadcasting - Google Patents

Abstract

The present disclosure relates to a method for monitoring quality of sign language broadcasting and an apparatus thereof. According to one embodiment of the present disclosure, the method for monitoring quality of sign language broadcasting comprises the following steps: generating a captured image of broadcast content; detecting a sign language region in the captured image; determining whether the captured image belongs to a non-sign language time when the sign language region is detected in the captured image; and determining quality of sign language broadcast of the broadcast content based on at least one of broadcast schedule information, signaling information, a monitoring unit object, or a monitoring detailed unit object related to the captured image on accumulated result data by repeating the generation step, the detection step, and the determination step for each predetermined capturing period.

Description

[0001] METHOD AND APPARATUS FOR MONITORING QUALITY OF SIGNAL LANGUAGE BROADCASTING [0002]

The present disclosure relates to sign language broadcasts, and more particularly, to a method and apparatus for monitoring the quality of sign language broadcasts.

Recently, support for broadcasting supplementary services for the disabled has been increasing. For example, broadcast supplementary services for hearing-impaired people are increasing, such as providing subtitles for broadcast content, providing screen commentary information, or providing a sign language interpretation screen. In addition, the Broadcasting and Communications Commission has set goals to increase the programming ratio of caption, screen commentary, and sign language interpretation.

In order to monitor whether or not such sign language broadcast is provided, it remains at a level where the non-handicapped person manually examines some samples while watching the broadcast. In other words, there has not yet been a method for automatically monitoring the quality of a sign language broadcast.

SUMMARY OF THE INVENTION It is a technical object of the present disclosure to provide a method and apparatus for detecting a hydration region in a sign language broadcast.

It is another object of the present disclosure to provide a method and apparatus for measuring the hydration time in a sign language broadcast.

A further technical object of the present disclosure is to provide a method and apparatus for determining the quality of a sign language broadcast.

The technical objects to be achieved by the present disclosure are not limited to the above-mentioned technical subjects, and other technical subjects which are not mentioned are to be clearly understood from the following description to those skilled in the art It will be possible.

According to an aspect of the present disclosure, a method for monitoring the quality of a sign language broadcast includes: generating a captured image of broadcast content; Detecting a hydration region in the captured image; Determining whether the captured image belongs to a non-hydration time when a hydration region is detected in the captured image; And repeating the generation step, the detection step, and the determination step for each predetermined capture period to generate at least one of broadcast programming information, signaling information, monitoring unit targets, or monitoring detailed unit targets related to the captured video And determining a quality of a sign language broadcast of the broadcast content based on the received broadcast content.

The features briefly summarized above for this disclosure are only exemplary aspects of the detailed description of the disclosure which follow, and are not intended to limit the scope of the disclosure.

According to the present disclosure, a method and apparatus for detecting a hydration region in a sign language broadcast can be provided.

According to the present disclosure, a method and apparatus for measuring the hydration time in a hydration broadcast can be provided.

According to the present disclosure, a method and apparatus for determining the quality of a sign language broadcast can be provided.

The effects obtainable from the present disclosure are not limited to the effects mentioned above, and other effects not mentioned can be clearly understood by those skilled in the art from the description below will be.

1 and 2 are views showing an exemplary configuration of a sign language broadcast quality monitoring apparatus according to the present disclosure.
3 is a diagram for explaining a hydration area detection scheme according to the present disclosure;
Figs. 4 and 5 are diagrams illustrating examples of a hydration time detection scheme according to the present disclosure. Fig.
6 is a flow chart for explaining the operation of the collecting apparatus according to the present disclosure;
7 is a flowchart illustrating an operation of the analysis server according to the present disclosure.

Hereinafter, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings, which will be easily understood by those skilled in the art. However, the present disclosure may be embodied in many different forms and is not limited to the embodiments described herein.

In the following description of the embodiments of the present invention, a detailed description of known functions and configurations incorporated herein will be omitted when it may make the subject matter of the present disclosure rather unclear. Parts not related to the description of the present disclosure in the drawings are omitted, and like parts are denoted by similar reference numerals.

In the present disclosure, when an element is referred to as being "connected", "coupled", or "connected" to another element, it is understood that not only a direct connection relationship but also an indirect connection relationship May also be included. Also, when an element is referred to as " comprising "or" having "another element, it is meant to include not only excluding another element but also another element .

In the present disclosure, the terms first, second, etc. are used only for the purpose of distinguishing one element from another, and do not limit the order or importance of elements, etc. unless specifically stated otherwise. Thus, within the scope of this disclosure, a first component in one embodiment may be referred to as a second component in another embodiment, and similarly a second component in one embodiment may be referred to as a first component .

In the present disclosure, the components that are distinguished from each other are intended to clearly illustrate each feature and do not necessarily mean that components are separate. That is, a plurality of components may be integrated into one hardware or software unit, or a single component may be distributed into a plurality of hardware or software units. Thus, unless otherwise noted, such integrated or distributed embodiments are also included within the scope of this disclosure.

In the present disclosure, the components described in the various embodiments are not necessarily essential components, and some may be optional components. Thus, embodiments consisting of a subset of the components described in one embodiment are also included within the scope of the present disclosure. Also, embodiments that include other elements in addition to the elements described in the various embodiments are also included in the scope of the present disclosure.

The definitions of the terms used in the present disclosure are as follows.

- Sign language broadcast: Broadcast content that contains video including the sign language area, or the transmission of such broadcast content.

- Sign language: Sign language.

- Sign language area: The area where the sign language is displayed on the sign language video.

- Listener: An object that displays the sign language behavior in a sign language video. The signer is usually a person, but may be replaced by a graphical representation of the person.

- Sign language background: The sign language area except the part recognized as sign language.

- Signature Time: The time sign language is provided in the sign language broadcast.

- Dehydration time: The remaining time except sign language time in sign language broadcasting.

- Sign language broadcast quality: A value indicating the degree to which a valid sign language service is provided, based on the presence or absence of the sign language area, the sign language, the sign language, and the sign language.

The definitions of the above terms are merely illustrative, and the scope of the present invention is not limited by these definitions. For example, the definition of such terms does not exclude the basic meaning that is easily understood by those skilled in the art.

In the following, various examples of this disclosure for a method and apparatus for monitoring the quality of a sign language broadcast according to the present disclosure will be described.

The Korea Communications Commission (KCC) considers that broadcasters should provide various supplementary services for people with disabilities with the aim of improving broadcasting services for people with disabilities. For example, an obligation provider to provide broadcasting for the hearing impaired was selected, and the selected provider achieved a predetermined target for the programming ratio of subtitles, screen commentary, and sign language interpretation. However, the Broadcasting and Communications Commission has reduced the criteria for selecting the broadcasting companies for the broadcasting of audiovisuals for the disabled, postponing the target of achieving the programming ratio target of caption, screen commentary, and sign language interpretation for two to three years. The main content of this amendment is to reduce the scope and scope of broadcasting service providers and to postpone the recommendation for two or three years in consideration of the poor realistic broadcasting environment. In other words, terrestrial broadcasters such as KBS, MBS and SBS had to achieve 100% subtitles, 5% sign language interpretation and 10% commentary until 2014 by 2013, but this goal was postponed until 2016. In addition, by 2016, pay-TV programs such as satellite broadcasting and jongbyeon should have 70 ~ 100% of subtitles, 5 ~ 7% of screen commentary and 3 ~ 5% of sign language interpreter.

The Broadcasting Commission said, "Due to the financial situation of the broadcasters who are suffering from the poor infrastructure of broadcasting production for the disabled,

One of the reasons for delaying the application of the standard for compulsory broadcasting standards is that there is no way to automatically evaluate the quality of sign language broadcasts. That is, until now, the non-disabled people have been watching the broadcasts directly, mainly by the disabled people's association, etc., passively investigating whether caption, screen commentary, sign language interpretation, etc. are provided. It can not be done. Therefore, it is still a matter of investigating according to some sampling standards.

In order to solve such a problem, the present invention provides a method for automating the monitoring of the sign language broadcast quality, which is one of the broadcast services for the disabled person, so that it is possible to investigate the quality of the sign language broadcast over the entire broadcast time for all the broadcast channels Can be provided.

1 and 2 are views showing an exemplary configuration of a sign language broadcast quality monitoring apparatus according to the present disclosure.

According to the current broadcast standard, the broadcast transmission signal itself does not include information indicating whether the broadcast includes the sign language broadcast. Also, the signaling information of the broadcast signal may include information on the presence or absence of the screen commentary audio and / or closed caption and the quality, but the broadcast signaling information for the sign language broadcast is not included in the transport stream (TS) .

Accordingly, it is possible to use the broadcast program information (e.g., channel, program name, broadcast date, program start time and end time) and signaling information (for example, a complicated transport stream TS belonging to a multiplexed program) , It is necessary to determine whether or not a sign language broadcast is to be made by analyzing the sign language broadcast image based on the metadata of the program information necessary for the sign language broadcast.

Accordingly, the apparatus for monitoring the quality of a sign language broadcast according to the present disclosure may include a collection device 100 and an analysis server 200. Based on one or more images captured by each of the collection devices 100 on the basis of a broadcast program, the analysis server 200 analyzes the quality of the received broadcast programs (for example, presence or absence of a sign language area, Specific gravity, hydration provision frequency, etc.) can be determined.

1 and 2, the apparatus for monitoring the quality of a sign language broadcast may include N collection devices 100_1, 100_2, ..., 100_N and an analysis server 200. [

Referring to FIG. 1, in N collecting apparatuses 100_1, 100_2, ..., 100_N, N may be a natural number of 1 or more. Further, each of the N collecting apparatuses 100_1, 100_2, ..., 100_N may correspond to one monitoring unit object. That is, the N collecting apparatuses 100_1, 100_2, ..., 100_N collect information on N monitoring unit targets at the same time.

For example, a monitoring unit target can be defined as a region, a channel, a time, a program, and a type unit. For example, N may correspond to the number of broadcasting areas to be monitored, the number of broadcasting channels, the number of broadcasting times, the number of broadcasting programs, and the number of broadcasting types (e.g., news, entertainment, education, etc.).

Each collection device 100 may include M demux / tuner modules 110, a storage module 120, and a collection management module 130.

In the M demux / tuner module 110, M may be a natural number greater than or equal to one. In addition, each of the M demux / tuner modules 110 may correspond to one monitoring subunit object. That is, the M demux / tuner modules 110_1, 110_2, ..., 110_M can simultaneously collect information on M monitoring subunits.

If the monitoring unit target is determined as one of the area, channel, time, program, or type, the monitoring unit target can be determined as the remaining one. Thus, monitoring for any combination of region, channel, time, program, or type is possible. For example, any combination may be defined such that all monitored objects, which are organized or can be organized into sign language broadcasts, can be traced in whole numbers.

For example, if the monitoring unit target is a region, the monitoring unit target can be defined as a channel, time, program, or type.

For example, if the monitoring unit target is a channel, the monitoring unit target can be defined as a region, time, program, or type.

For example, if the monitoring unit target is time, the monitoring unit target can be defined as a region, a channel, a program, or a type.

For example, if the monitoring unit target is a program, the monitoring unit target can be defined as a region, a channel, a time, or a type.

For example, if the monitoring unit target is a type, the monitoring unit target can be defined as a region, a channel, a time, or a program.

In addition, the number of the demux / tuner modules 110 included in each of the plurality of collecting apparatuses 100 may be the same or different from each other. For example, the number of the demux / tuner modules 110 included in the first collecting device 100_1 and the number of the demux / tuner modules 110 included in the second collecting device 100_2 are the same It may or may not be the same.

Each of the demux / tuner modules 110 may capture a moving image corresponding to the broadcast content from the received broadcast signal at predetermined intervals, and may transmit the captured image to the storage module 120. Each demux / tuner module 120 analyzes a transport stream (TS) of a received broadcast signal and transmits PSIP (program and system information protocol) and / or PSI (program specific information) information to a collection management module 130).

The storage module 120 may store and manage captured images of the sign language broadcast content obtained from the demux / tuner module 110 for each of the monitoring unit object and the monitoring detailed unit object. For example, the storage module 120 may store and manage captured images of corresponding broadcast content for any combination of region, channel, time, program, or type.

In addition, the storage module 120 may store the broadcast program information (PSIP) and the signaling information (PSI) together with the captured image.

The collection management module 130 may manage the broadcasting program organizing information and the program signaling information for each of the monitoring unit object and the monitoring detailed unit object based on the PSIP and / or PSI information obtained from the demux / tuner module 110 . For example, the collection management module 130 may manage program information and program signaling information for each combination of region, channel, time, program, or type.

In addition, the collection management module 130 may obtain PSIP from Web EPG (Electronic Program Guide) information.

Also, the collection management module 130 may control the demux / tuner module 110 to analyze signaling information (PSI) for each monitoring unit object and each monitoring unit object.

The collection management module 130 may transmit analysis results obtained by analyzing broadcast programming information (PSIP) and signaling information (PSI) stored in the storage module 120 to the analysis server 200 together with the broadcast content capture images.

2, the analysis server 200 may include an analysis management module 210, a statistics module 220, a data analysis module 230, and a database 240.

The analysis management module 210 may receive the monitoring results performed in each of the N collecting devices 100_1, 100_2, ..., 100_N according to a predetermined period. Here, the monitoring result may include a sign language broadcast content capture image and related information. Here, the related information may include at least one of a monitoring unit object, a monitoring subunit object, a broadcast programming information (PSIP), or signaling information (PSI) including the captured image.

The analysis management module 210 may also store the received monitoring results in the database 240.

In addition, the analysis management module 210 may analyze the received monitoring results and periodically check whether there is an error in the collection device 100. [

The statistical module 220 can collect and manage analysis results of the data analysis module 230 for each of the monitoring unit object and / or the monitoring detailed unit object.

The data analysis module 230 may analyze the monitoring results of the monitoring unit targets and / or monitoring detailed unit targets stored in the database 240 in real time or in non-real time, and may store the analysis results in the database 240.

In addition, the data analysis module 230 may analyze the monitoring result to determine the presence or absence of the sign language area, the sign language operation status, the sign language scopes, and the sign language sign language.

3 is a diagram for explaining a hydration area detection scheme according to the present disclosure;

The sign language area detection method described with reference to FIG. 3 is a method in which a broadcast content (for example, PSIP, PSI or the like) or a separate information (for example, EPG information) Or if it is unknown where the sign language area is located in the broadcast content. However, the scope of the present disclosure is not limited thereto, and the examples described with reference to FIG. 3 may be applied for verification even when the sign language area can be determined by a broadcast signal or separate information.

Although various complex image analysis algorithms defined in image processing field can be used to analyze sign language, there is no need to use complicated or high-level hardware or software resources for analyzing sign language images. Thus, the present disclosure describes examples of simple and efficient analysis of a sign language image.

In particular, the present disclosure describes examples of identifying or detecting a hydration region in a captured image.

Color analysis and face recognition can be applied to detect the hydration region.

First, the color analysis is explained.

The amount of color change can be measured on a pixel-by-pixel basis for a plurality of images periodically captured during a period between the start of the broadcast program and the end of the broadcast program. The amount of color change can be measured according to HSV (Hue Saturation Value), RGB (Red Green Blue), or YUV (luminance and color difference) standards.

Next, an area having a small amount of color change can be detected based on a predetermined color change amount threshold value. Here, an area having a small amount of change in color means that there is a high probability that the same object exists at the same position in the image. Accordingly, the detected region can be determined as the hydration region candidate.

In addition, the predetermined color variation threshold may be set differently according to the broadcasting company, the broadcasting program, the broadcasting type, and the like. For example, in the case of an entertainment program, since it is expected that the amount of color change is large in most areas compared to the news program, the threshold value for the entertainment program may be set lower than the threshold value for the news program.

Next, the face recognition will be described.

The face detection can be attempted for each of the marsh region candidates detected in the captured image through the color analysis as described above. As a result, the region in which one face is detected from among the hydration region candidates can finally be determined as the hydration region.

In the example of FIG. 3, it is assumed that the first mating area candidate 310 and the second mating area candidate 320 having a color variation amount less than a predetermined threshold value are detected in the captured image 300. More specifically, the first and second mating area candidates 310 and 320 may correspond to an area having a small amount of color change over a plurality of captured images, that is, an area where the same object is fixedly located at the same position.

Next, face detection may be attempted for each of the first and second mating area candidates 310 and 320. [ Since one face is detected in the first mating area candidate 310, it can be finally determined to be the mating area. Since the second recognition area candidate 320 fails to recognize the face, it can be determined that it is not the sign language area.

In addition, the sign language area pattern matching test may be performed instead of the face recognition. Specifically, it is possible to check whether or not a mating area candidate that is detected as having a small amount of color variation matches a predetermined mating area pattern. For example, a predetermined sign language area pattern can be set as a blue oval background. In the example of FIG. 3, since the background part of the blue ellipse is matched with a predetermined ratio (for example, 50%) or more as compared with the predetermined sign language area pattern, the first sign language area candidate 310 is finally the sign language area You can decide. Since the ratio of the second hydration area candidate 320 to the predetermined hydration area pattern is low, it can be determined that the second hydration area candidate 320 is not the hydration area.

Here, an example of a predetermined sign language area pattern is not limited to a blue ellipse. For example, the degree of matching with another pattern (for example, a black rectangle) may be checked according to a broadcasting company, a broadcasting program, a broadcasting type, and the like. That is, the scope of the present disclosure is not limited to the example of a predetermined hydration area pattern, but includes various schemes of hydration area detection using the degree of matching with a predetermined hydration area pattern.

Figs. 4 and 5 are diagrams illustrating examples of a hydration time detection scheme according to the present disclosure. Fig.

In order to detect the hydration time, it is possible to apply a scheme excluding the non-hydration time from the time when the hydration region exists. Examples for detecting the non-hydration time for this purpose are described below.

The example of FIG. 4 is for measuring a sign language time or a sign language time based on hand position recognition or hand gesture recognition. For example, the hand of the listener can be recognized and the position of the recognized hand can be analyzed at predetermined intervals.

Further, the time point at which the hand of the receiver is recognized may be included at the time when the face of the receiver is recognized in the sign language area. That is, the point in time when the face of the listener is not recognized can be determined as the non-signifying time even if the hand position is not recognized, and the non-signifying time or the sign language time can be determined based on the hand position recognition at the time when the face of the signee is recognized .

In the example of Fig. 4, at the time point t-1, since the position of the recognized hand is the left and right of the stop, which is outside the bottom center of the hydration area, it can be determined to belong to the hydration time.

Next, at the time point of t and t + 1, since the position of the hand recognized is the bottom center of the hydration region, it can be determined to belong to the non-hydration time.

Next, at the time point t + 2, it is determined that the position of the recognized hand belongs to the hydration time since the position of the recognized hand is the stopping center outside the bottom center of the hydration area.

That is, the time when the position of the object recognized by the hand of the listener is located at the center of the lower end of the sign language area is determined as the non-sign language time, and during the time when the sign language area exists, You can decide by time.

The example of FIG. 5 is for a method of measuring the hydration time or the non-hydration time based on the color recognition. For example, it is possible to recognize the color of a specific subregion in the hydration region, and to analyze at every predetermined cycle whether or not the recognized color matches the color of the hand of the recipient.

Further, the time point at which the color of the specific sub region in the sign language area is recognized may be included at the time when the face of the sign language is recognized in the sign language area. That is, the point in time when the face of the listener is not recognized can be determined as the non-sign language time even if the color of the specific sub-region is not recognized, and when the face of the listener is recognized, It can be decided whether or not it is time.

In the example of FIG. 5, since the specific value of the color value of the hand of the handler is low in a specific sub-area at the bottom center of the hydration area at the time of t-1, it can be determined to belong to the hydration time.

Next, since the specific value of the color value of the hand of the handler is high in the specific sub-area at the center of the lower end of the hydration area at time t and t + 1, it can be determined to belong to the non-hydration time.

Next, at the time point t + 2, since the weight of the hand value of the hand of the handler is low in a specific sub area at the lower center of the hand sign area, it can be determined to belong to the hand sign time.

That is, if the color of a certain sub region (for example, the lower center) in the hydration region is analyzed and the time occupied by the color similar to the color value of the hand of the receiver is higher than the predetermined threshold value, Time can be determined. Accordingly, it is possible to determine, as the hydration time, the remainder excluding the non-hydration time during the time when the hydration area exists in the entire program provision time.

In order to apply the example shown in Fig. 5, the receiver can be clearly distinguished from the background of the sign language area (for example, blue), and can have a color dress clearly distinguished from the face and hands of the listener.

As a further example, the hydration time may be measured based on the motion vector.

The motion vector is a vector representing a displacement of a specific position in an image at a first view point from an image at a second view point. In the present disclosure, a motion vector based on a displacement of a position of each of a plurality of minutiae points (for example, pixel units) in a hydration region of a captured image at a first time point in a captured image at a second time point is measured, It is possible to determine whether the value of the scalar sum of the motion vectors for the motion vectors is below a predetermined threshold.

If the sum of the motion vectors is less than or equal to the threshold value, it can be regarded as a time without the hydration operation of the receiver. Therefore, the time between the first time and the second time can be determined as the non-hydration time. Accordingly, it is possible to determine, as the hydration time, the remainder excluding the non-hydration time during the time when the hydration area exists in the entire program provision time.

If the sum of the motion vectors exceeds the threshold value, since the hydration operation of the receiver can be regarded as a time, the time between the first time and the second time may be determined as the hydration time.

6 is a flow chart for explaining the operation of the collecting apparatus according to the present disclosure;

In step S610 of FIG. 6, the collecting apparatus 100 may acquire broadcast program information (e.g., channel information, program name, broadcast date, program start time, program end time, etc.). For example, such a broadcast programming information (or PSIP) may be obtained directly from the web EPG by the collection management module 130, or the PSIP information obtained by the demux / tuner module 110 by receiving and analyzing the broadcast signal To the collection management module 130.

In step S620, the collecting apparatus 100 transmits signaling information on a monitoring unit target and / or a monitoring subunit object (for example, meta data representing program information necessary for a complicated transport stream TS belonging to a multiplexed program in a table format) ) Can be analyzed. For example, the acquisition management module 130 may control the demux / tuner module 110 to analyze the signaling information (or PSI) by any combination of region, channel, time, program, or type.

In step S630, the collecting apparatus 100 may periodically capture a broadcast program screen. For example, the demux / tuner module 110 may generate a captured image at predetermined intervals during a broadcast program providing time.

In step S640, the collecting apparatus 100 may store related information of the captured image while storing the captured image. For example, the storage module 120 may store one or more of a monitoring unit object, a monitoring unit object, a PSIP, or a signaling information (PSI) including the captured image as related information together with the captured image Can be stored.

In step S650, the collecting apparatus 100 may transmit the captured captured image and related information to the analysis server 200. [ Also, the collection device 100 may transmit the analysis result of the related information of the captured image to the analysis server 200. [ For example, for example, the collection management module 130 may include a capture image, associated information (e.g., one or more of a monitoring unit target, a monitoring unit target, a PSIP, or a PSI) stored in the storage module 120, And transmit the analysis result to the analysis management module 210 of the analysis server 200.

The result of the analysis may include error information on the relevant information. For example, the analysis result may include information indicating whether there is an error in the signaling information, an error in the case of an error, and the like.

In the example of Fig. 6, the collecting apparatus can perform the operations of steps S630 to S650 repeatedly at predetermined capture periods.

Alternatively, steps S630 and S640 may be performed for each predetermined capture period, and in step S650, a plurality of captured images, related information, and analysis results corresponding to a plurality of capture periods cumulatively stored may be transmitted to the analysis server 200 at one time have.

7 is a flowchart illustrating an operation of the analysis server according to the present disclosure.

In step S710 of FIG. 7, the analysis server 200 may receive the captured image, the related information, and the analysis result from the collection device 100. FIG. For example, the analysis management module 210 may receive captured images, related information, and analysis results transmitted from the collection management module 130 of the collection device 100.

In step S720, the analysis server 200 may store the received data. For example, the analysis management module 210 may store the received data (e.g., captured images, related information, and analysis results) in the database 240.

In step S730, the analysis server 200 may analyze the stored data. For example, data analysis module 230 may analyze stored data (e.g., captured images, related information, and analysis results).

In addition, the data analysis module 230 may determine whether or not a sign language area exists in the captured image of the stored data. For example, the data analysis module 230 may determine whether there is a sign language area in the captured image based on broadcast programming information and / or signaling information. For example, the data analysis module 230 may determine whether or not a sign language area exists in the captured image based on a method such as color analysis, face recognition, pattern matching, and the like (see an example of FIG. 3).

In addition, the data analysis module 230 may determine whether the captured image of the stored data belongs to the hydration time or the de-hydration time. For example, the data analysis module 230 may determine whether the captured image belongs to a sign-on time or a sign-off time based on broadcast programming information and / or signaling information. For example, the data analysis module 230 may determine whether the captured image belongs to the hydration time or the non-hydration time on the captured image based on a method such as hand position recognition, color recognition, and motion vector analysis And the example of Fig. 5).

The data analysis module 230 analyzes the captured image analysis result of the stored data (for example, the presence of a sign language broadcast, the quality of a sign language broadcast, etc.) with related information (for example, a monitoring unit target, PSI < / RTI > in the database 240).

In addition, the data analysis module 230 may delete the captured image if the captured image is not a sign language broadcast.

In step S740, the analysis server 200 may aggregate and manage analysis results for each monitoring unit object and / or each monitoring unit object.

For example, the statistics module 220 may aggregate analysis results by any combination of region, channel, time, program, or type and output it to the screen according to the user's request. For example, the quality of a sign language broadcast can be expressed by a value of a sign language provision frequency, and a sign language provision frequency can be expressed by a numerical value such as a distribution of a sign language time, a distribution of a sign language time,

The operations of steps S710 to S740 in FIG. 7 may be performed periodically, and information corresponding to a plurality of capture periods may be received at one time, and storage, analysis, and statistical calculation may be performed at one time. Alternatively, steps S710 to S730 of FIG. 7 may be repeatedly performed at each capture period, and step S740 may be performed at a time based on data accumulated and stored after completion of the plurality of capture periods.

According to the present disclosure, it is possible to provide a new image analysis method for sign language broadcast, and thus it is possible to objectively and automatically check whether the sign language broadcast is organized, and to verify the quality of sign language broadcast. Therefore, by installing and operating the device for monitoring the quality of the sign language broadcasts according to the present invention nationwide, it can be utilized for selecting the obligation service provider for the broadcasting of the disabled and verifying whether or not the target is achieved.

Although the exemplary methods of this disclosure are represented by a series of acts for clarity of explanation, they are not intended to limit the order in which the steps are performed, and if necessary, each step may be performed simultaneously or in a different order. In order to implement the method according to the present disclosure, the illustrative steps may additionally include other steps, include the remaining steps except for some steps, or may include additional steps other than some steps.

The various embodiments of the disclosure are not intended to be all-inclusive and are intended to illustrate representative aspects of the disclosure, and the features described in the various embodiments may be applied independently or in a combination of two or more.

In addition, various embodiments of the present disclosure may be implemented by hardware, firmware, software, or a combination thereof. In the case of hardware implementation, one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays A general processor, a controller, a microcontroller, a microprocessor, and the like.

The scope of the present disclosure is to be accorded the broadest interpretation as understanding of the principles of the invention, as well as software or machine-executable instructions (e.g., operating system, applications, firmware, Instructions, and the like are stored and are non-transitory computer-readable medium executable on the device or computer.

100 ... collecting device
110 ... demux / tuner module
120 ... storage module
130 ... collection management module
200 ... Analysis Server
210 ... analysis management module
220 ... Statistical module
230 ... Data Analysis Module
240 ... database
300 ... capture video
310 ... First sign language candidate
320 ... second sign language candidate

Claims (1)

A method for monitoring sign language broadcast quality,
Generating a captured image of broadcast content;
Detecting a hydration region in the captured image;
Determining whether the captured image belongs to a non-hydration time when a hydration region is detected in the captured image; And
Wherein the generation step, the detection step, and the determination step are repeated for each predetermined capture period to generate cumulative result data based on at least one of broadcast programming information, signaling information, monitoring unit targets, And determining a sign language broadcast quality of the broadcast content.

Images