JP2006154976A - Animation frame analyzer - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To resolve a problem when extracting necessary information such as an address of a postcard from a displayed image plane of a program or the like, that since signboards and logotype information on clothes of the cast that are not too necessary are included in the image plane, it is difficult to extract a particular the necessary information from the image, and it is difficult to operate the designation of an extraction area or the like of information by a portable apparatus or the like. <P>SOLUTION: In an animation frame information analyzer, an area with little movement in a plurality of frames of animation is detected, and pattern information such as character information in the area (an immobile area) with little movement is extracted. Since information necessary for a viewer is frequently displayed in a form of a telop or the like, it can be conceived that its amount of movement is small unlike an amount of the movement of characters of a signboard or characters on clothes that are moved by the movement of a camera or the like. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a technique for acquiring information such as an e-mail address displayed in a moving image.

Currently, for example, a complaint or opinion contact address, a present application address or an e-mail address is often displayed in a television program or video software. The viewer writes down the information displayed in the video and makes a call or sends a postcard or an e-mail to the written contact or destination. In Patent Document 1, in order to save the trouble of writing down information, an image including character information such as an e-mail address is acquired from a display screen, and the address information is extracted from the image. Has disclosed a technique of sending an e-mail.
JP 2001-167026 A

  However, in the above prior art, it is necessary for a user or the like to specify an area including character information such as an e-mail address in the image, which is troublesome for the viewer or is difficult to specify on a portable device. There is a problem. In addition, when extracting character information without designation, character information that is not usually related to the viewer is included on the display screen of the program, for example, character information on the clothes of the signboard or performers, There is also a problem that it is difficult to extract specific character information from the image on the display screen.

  In order to solve the above-described problems, the present invention determines a region with less motion in a plurality of frames of a motion image and extracts pattern information such as character information in the region with less motion (non-moving region). A frame information analysis apparatus is provided. This is because information such as addresses and e-mail addresses that are necessary for viewers is often displayed in the form of telops, etc. Therefore, the amount of movement such as characters on signboards and characters on clothes that move when the camera moves This is because the amount of movement is considered to be small.

  Specifically, a moving image frame information acquisition unit that acquires a plurality of moving image frame information, a fixed region detection unit that detects a fixed region in the plurality of moving image frame information, and a fixed region detected by the fixed region detection unit A moving picture frame information analyzing apparatus having a pattern information extracting unit that extracts pattern information from the video information shown in FIG.

  According to the present invention configured as described above, the viewer can easily acquire various information such as an e-mail address without performing a special operation such as designation of an image area. This is particularly effective in extracting information in a moving image in a small device such as a mobile phone in which region designation is difficult.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings. Note that the present invention is not limited to these embodiments, and can be implemented in various modes without departing from the spirit of the present invention. The first embodiment will mainly describe claims 1, 5, 6, 7, and 8. In the second embodiment, claims 2 and 9 will be mainly described. In the third embodiment, claim 3 will be mainly described. In the fourth embodiment, claim 4 will be mainly described.

  First Embodiment <Concept of First Embodiment> FIG. 1 is a diagram for explaining an example of a concept of a moving image frame analyzing apparatus in the present embodiment. As shown in this figure, first, a “request destination” is displayed together with a talk pattern by the presenter in a certain scene of a certain music program. The moving picture frame analysis apparatus of the present embodiment can extract only the information of “request destination” by analyzing the moving picture frame of the music program. Therefore, since the information can be easily extracted by the moving picture frame information analysis apparatus of the present embodiment, it is possible to save the trouble of writing down information such as “destination of request” on paper one by one.

    <Configuration of Embodiment 1> FIG. 2 is a diagram illustrating an example of functional blocks in the moving image frame analysis apparatus of the present embodiment. As shown in this figure, the “moving picture frame analyzing apparatus” (0200) of the present embodiment includes a “moving picture frame information acquiring unit” (0201), a “non-moving region detecting unit” (0202), and a “pattern information extracting unit”. (0203). Note that the functional blocks of the system described below can be realized as hardware, software, or both hardware and software. Specifically, if a computer is used, such as a CPU, a memory, a bus, a hard disk drive, a reading drive such as a CD-ROM or a DVD-ROM, a transmission / reception port for various communications, an interface, and other peripheral devices. Examples include a hardware configuration unit, a driver program for controlling the hardware, and other application programs. Specifically, the functions of the respective units are realized by sequentially executing the programs developed on the memory, by processing, storing, and outputting data on the memory and data input through the interface. Further, the present invention can be realized not only as an apparatus or a system but also as a method. In addition, a part of the invention can be configured as software. Furthermore, a software product used for causing a computer to execute such software and a recording medium in which the product is fixed to a recording medium are naturally included in the technical scope of the present invention (the same applies throughout the present specification). Is).

  The “video frame information acquisition unit” (0201) has a function of acquiring a plurality of video frame information. “Movie frame information” refers to information for displaying one frame (one frame) constituting a movie, and a plurality of frames based on this movie frame information are output in succession to be reproduced as a series of movies. it can. FIG. 3 is a diagram for explaining an example of a frame displayed by moving image frame information. As shown in this figure, there are three frames displayed by three moving image frame information. Then, by displaying these three frames in the order of first, second, and third within 0.1 seconds, for example, it can be recognized as a moving image by human eyes. The video composed of this video frame information is displayed after the host of the program wearing a costume with the logo “music soul” moves from left to right while “request destination” is displayed at the bottom right of the screen. It ’s a video that comes back to the middle.

  Each piece of moving picture frame information may be information capable of displaying one frame independently, or in the case of a compressed moving picture, information that can display one frame with reference to the preceding and following moving picture frame information. It may be. “Acquiring a plurality” may be a form of acquiring a plurality of pieces of moving picture frame information in which the display order of frames is continuous. If each piece of moving picture frame information is independent information (uncompressed moving picture information). If this is the case, a plurality of pieces of discontinuous video frame information may be acquired. The moving picture frame information is a concept including moving picture frame information of either interlaced or non-interlaced moving picture format. In that case, the odd-numbered frame and the even-numbered frame in the interlaced video may be processed as different video frame information, or both are processed as a single video frame information (with non-interlace processing). May be.

  In addition, the moving image frame information acquired by the moving image frame information acquisition unit may be moving image frame information of a moving image reproduced from a recording medium such as a DVD or a video, or may be television broadcast reception or cable reception. It may be moving image frame information of a moving image acquired via a tuner, or moving image frame information of a moving image distributed by streaming or downloading on the Internet. When the moving image frame information is analog data, it needs to be converted into digital data by an A / D (analog / digital) converter in order to detect a non-moving area and extract pattern information described later.

  The “non-moving region detection unit” (0202) has a function of detecting a non-moving region. The “non-moving region” refers to a region with little movement among the plurality of moving image frame information. For example, in the three pieces of moving image frame information shown in FIG. 3, the area where “request destination” is displayed hardly moves from the lower right position of the screen and can be said to be a non-moving area. On the other hand, it can be said that the other parts in FIG. 3 are not in a non-moving area because the presenter is moving around in the screen.

  FIG. 4 is a diagram for explaining an example of detection of a non-moving area in the non-moving area detecting unit. As shown in this figure, the two frames (a) and (b) indicated by the first and second moving image frame information are divided into predetermined areas such as 4 × 4. Then, in each region, for example, it is determined whether the ratio of the color information (RGB, YUV, etc.) constituting the same, the integral value of the luminance in the region, and the like are the same or approximate. Or if it is a compression moving image, you may judge the motion amount of the area | region from the difference information of the motion in each area | region. For example, in the area 403A in the frame (a) in FIG. 4 and the corresponding area 403B in the subsequent frame (b), the former includes information for displaying a part of the human face. However, it is not included in the latter, but instead includes information for displaying a program mascot or the like hidden in the background of the person. Therefore, since the information indicating 403A and 403B is greatly different, it is determined that this area 403 is not a non-moving area. On the other hand, both 401A and 401B include information for displaying “destination of request” and “〒 110-xxxx”. Therefore, the information indicating 401A and 401B is approximate, and it can be determined that this area is a non-moving area. This determination is performed for each region, and the region determined to be a non-moving region is detected.

  If the pattern information (details will be described later) to be extracted from the non-moving area is information consisting of characters such as an e-mail address or a postal address, the edge component is strong as a feature of the video information of the area including the characters. Is mentioned. Accordingly, the edge component amount in the area may be calculated using a technique such as hill climbing control of autofocus, and it may be determined that the area above the threshold includes characters and detected as a non-moving area.

  By detecting the immovable area in this way, it is possible to specify an area in which character information such as a telop is displayed on the screen. The shirt logo “music soul” in the area where the presenter is not detected as the immovable area does not have to be extracted as pattern information to be described later.

  The “pattern information extraction unit” (0203) has a function of extracting pattern information from the video information indicated in the non-moving area detected by the non-moving area detection unit (0202). “Pattern information” refers to information that can be extracted according to a predetermined pattern, for example, contact information such as presents and opinions included in the immobile area as a telop, homepage, e-mail address, hourly report, breaking news, quiz problem, Or text information such as passwords. Other examples include bar code information and predetermined image information. The “predetermined pattern” includes, for example, 50 sounds, kanji, alphabets, numbers, pictograms, emoticons, predetermined images, etc., and is extracted by comparing with and referring to the predetermined pattern as will be described later. Characters in the images “now”, “day”, and “ha” are converted into text information and combined with “today” to generate pattern information.

  The extraction of the pattern information includes a method using an algorithm such as an optical character reader if it is text information. FIG. 5 is a diagram for explaining an example of pattern information extraction using the algorithm of the optical character reader. As shown in this figure, the non-moving area extracted from the moving picture frame information is basically video information. Therefore, when, for example, characters, which are images included in the video information, are extracted as text information, they are compared and collated with previously stored patterns for extracting characters such as 50 sounds, kanji, katakana, alphabet, and numbers. Then, it is determined which pattern for extraction is approximate from the overlap of the distribution states of the dots in both images. In the character extraction pattern, corresponding text information is stored in association with each other, and converted into text data. In this way, a plurality of characters that are images included in the video information can be extracted as text information. Then, the extracted characters are combined and extracted as pattern information. Of course, the character extraction patterns may be extracted as pattern information by using emoticons, pictograms, barcodes, or information indicating patterns of predetermined images. If the barcode information or image information is embedded with information such as a two-dimensional barcode or an email address, the barcode information or image information converted into information such as an email address is used as a pattern. You may perform the process extracted as information.

  In addition, by determining whether the text information extracted in this way is a text including an at sign (@), it is determined that the pattern information is an e-mail address, or more electronic information is extracted from the extracted text information. A function of extracting only specific pattern information such as only an e-mail address may be provided. FIG. 6 is a diagram for explaining an example when extracting only an e-mail address as pattern information. As shown in this figure, the information “xxx@xxx.xxx” (the number of x is not specified) is further retained as a matching pattern. Compare and collate with text information extracted from the immobile area. As a result, it is possible to extract pattern information excluding unnecessary messages other than e-mail addresses. Of course, as a pattern for collation, a homepage address may be extracted by “http”, or an address or the like may be extracted by a zip code (〒).

  In this way, it is possible to easily extract pattern information such as a mail address included in a portion where the motion of the moving image is small without special designation by the user.

    <Processing Flow of First Embodiment> FIGS. 7A and 7B are flowcharts showing an example of a processing flow in the moving picture frame analysis apparatus of the present embodiment. As shown in (a) of this figure, first, it is determined whether or not there is a processing start command (step S0701a). If there is a start command, moving image frame information is acquired, and it is determined whether a predetermined number of moving image frame information has been obtained (step S0702a). If the predetermined number has not been acquired, the moving image frame information acquisition process is performed again. On the other hand, when it is determined that a predetermined number of moving image frame information has been acquired, a non-moving region is detected from the acquired plurality of moving image frame information (step S0703a). Finally, pattern information is extracted from the video information indicated in the detected immovable area (step S0704a).

  Alternatively, as an example of the flow of other processing, as shown in FIG. 7B, it is first determined whether or not there is a processing start command (step S0701b). If there is a start command, a plurality of pieces of moving picture frame information are acquired (step S0702b). Subsequently, it is determined whether or not a non-moving area is detected in the acquired plurality of moving image frame information (step S0703b). If it is determined in step S0703b that a non-moving area has been detected, pattern information is extracted from the video information indicated in the detected non-moving area (step S0704b). On the other hand, if it is determined in step S0703b that a non-moving region has not been detected, a plurality of moving image frame information acquisitions in step S0702b are started again.

    <Simple explanation of the effect of the first embodiment> As described above, the moving picture frame analysis device of the present embodiment can display text information included in a non-moving area and displayed as a telop without any special operation by the user. It can be extracted easily.

  Embodiment 2 <Concept of Embodiment 2> FIG. 8 is a diagram for explaining an example of a concept of a moving image frame analysis apparatus according to the present embodiment. As shown in this figure, first, the moving picture frame analysis apparatus of the present embodiment extracts pattern information such as a destination of a request from a moving picture based on the moving picture frame analysis apparatus of the first embodiment. If the pattern information is information indicating an electronic mail address, a process of starting a mailer is performed. Furthermore, an e-mail input form in which the e-mail address of the destination of the request is input is activated. As described above, the moving image frame information analyzing apparatus can activate an application or the like in accordance with the pattern information.

    <Configuration of Second Embodiment> FIG. 9 is a diagram illustrating an example of functional blocks in the moving image frame analyzing apparatus according to the present embodiment. As shown in this figure, the “moving picture frame analysis device” (0900) of the present embodiment is based on the first embodiment, and “moving picture frame information acquisition unit” (0901) and “non-moving area detection unit” (0902). And a “pattern information extraction unit” (0903). The moving image frame analysis apparatus according to the present embodiment further includes a “per-pattern execution process identifier holding unit” (0904) and an “execution process identifier acquisition unit” (0905) as feature points. Note that the “moving image frame information acquisition unit”, “non-moving region detection unit”, and “pattern information extraction unit” have already been described in the description of the first embodiment, and thus description thereof is omitted here.

  The “per-pattern execution process identifier holding unit” (0904) has a function of holding predetermined pattern information and an execution process identifier in association with each other. FIG. 10 is a diagram for explaining the association between pattern information and an execution process identifier. As shown in this figure, for example, text information including a character string “*@*.*” (* is unspecified) as pattern information is associated with information for identifying “electronic mailer” as an execution processing identifier. It has been. Alternatively, the pattern information “http: // *” and the execution processing identifier of “Web browser”, the pattern information “zip code (〒)” and the execution processing identifier of “postcard (address) creation software”, or “050- The pattern information “*-*” and the “IP phone application” are associated with each other. A plurality of execution process identifiers may be associated with the pattern information. For example, in addition to “postcard (address) creation software” and “postal code (〒)” pattern information, an execution processing identifier of “electronic map” may be associated and selected when executing. Alternatively, as associations other than those shown in the figure, pattern information of a character string “earthquake” and an execution process identifier “access to earthquake early warning site” may be used.

  The “execution process identifier acquisition unit” (0905) has a function of acquiring the execution process identifier associated with the pattern information extracted by the pattern information extraction unit (0903) from the pattern-specific execution process identifier holding unit (0904). . Thus, for example, when text information including a character string “*@*.*” (* is unspecified) is extracted as pattern information, an identifier for identifying “electronic mailer” is acquired. Accordingly, it is possible to start an electronic mailer or an electronic mail input form in which an electronic mail address that is pattern information extracted in advance is input.

  Therefore, it is convenient because execution processing for automatically requesting a program, applying for a present, accessing an official homepage, etc. is automatically performed without taking notes one by one.

    <Processing Flow of Second Embodiment> FIGS. 11A and 11B are flowcharts showing an example of a processing flow in the moving picture frame analysis apparatus of the present embodiment. As shown in (a) of this figure, first, it is determined whether or not there is a processing start command (step S1101a). If there is a start command, moving image frame information is acquired, and it is determined whether a predetermined number of moving image frame information has been obtained (step S1102a). If the predetermined number has not been acquired, the moving image frame information acquisition process is performed again. On the other hand, when it is determined that a predetermined number of moving image frame information has been acquired, a non-moving region is detected from the acquired plurality of moving image frame information (step S1103a). Next, pattern information is extracted from the video information indicated in the detected immovable area (step S1104a). Finally, the execution process identifier associated with the pattern information extracted in step S1104a is acquired from the execution process identifier stored in advance in association with predetermined pattern information (step S1105a).

  Alternatively, as an example of another processing flow, as shown in FIG. 11B, first, it is determined whether or not there is a processing start command (step S1101b). If there is a start command, a plurality of pieces of moving picture frame information are acquired (step S1102b). Subsequently, it is determined whether or not a non-moving area is detected in the acquired plurality of moving picture frame information (step S1103b). If it is determined in step S1103b that a non-moving area has been detected, pattern information is extracted from the video information indicated in the detected non-moving area (step S1104b). Finally, the execution process identifier associated with the pattern information extracted in step S1104b is acquired from the execution process identifier previously stored in association with predetermined pattern information (step S1105b). On the other hand, if it is determined in step S1103b that a non-moving region has not been detected, a plurality of moving image frame information acquisitions in step S1102b is started again.

    <Simple Explanation of Effect of Second Embodiment> As described above, based on text information included in a non-moving area and displayed in a telop or the like by the moving picture frame analysis apparatus of the present embodiment, for example, an e-mail address It is possible to automatically process the activation of the electronic mailer, the activation of the Web browser if it is a homepage address, or the activation of address creation software or a printing apparatus if it is an address, without bothering the user.

  << Embodiment 3 >> <Concept of Embodiment 3> FIG. 12 is a diagram for explaining an example of a concept of a moving picture frame analysis apparatus according to the present embodiment. As shown in this figure, first, the moving picture frame analyzing apparatus according to the present embodiment is based on the moving picture frame analyzing apparatus according to the first embodiment or the second embodiment. Pattern information is extracted. At that time, the moving picture frame analyzing apparatus of the present embodiment displays the address of the program homepage and the password, for example, with a time lag as shown in the moving picture frame information when extracting pattern information as feature points. Even in this case, it can be extracted as one pattern information.

    <Configuration of Third Embodiment> FIG. 13 is a diagram illustrating an example of functional blocks in the moving image frame analyzing apparatus according to the present embodiment. As shown in this figure, the “moving picture frame analysis device” (1300) of the present embodiment is based on the first embodiment, and includes a “moving picture frame information acquisition unit” (1301) and a “non-moving region detection unit” (1302). And a “pattern information extraction unit” (1303). Of course, on the basis of the second embodiment, a “pattern-specific execution process identifier holding unit” and an “execution process identifier acquisition unit” (not shown) may be further included. In the moving image frame analysis apparatus according to the present embodiment, the “pattern information extraction unit” (1303) further includes “multi-region pattern information acquisition unit” (1304) as feature points. Note that the “moving image frame information acquisition unit”, “non-moving region detection unit”, and “pattern information extraction unit” have already been described in the description of the first embodiment, and thus description thereof is omitted here.

  When there are a plurality of immovable areas detected by the immovable area detection unit (1302), the “multiple area pattern information acquisition unit” (1304) extracts pattern information from each immovable area, and extracts one or more of them. It has a function of acquiring pattern information by combination. “A plurality of immovable regions” means a plurality of temporally or spatially. FIG. 14 is a diagram for explaining an example of acquisition of pattern information when there are a plurality of immovable areas in terms of time. As shown in this figure, “http://xxx.com” is extracted as pattern information from the video information of a certain immobile area A1 from time m to time n. Then, from the video information in the same immovable area A2 from time o to time p after time n, information indicating a password for logging in to the homepage of the homepage address, which is “password: 123xx456”, is now obtained. Extracted as pattern information. In such a case, the pattern information of “http://xxx.com password: 123xxx456” is acquired by combining both of them.

  When combining a plurality of pattern information extracted from the plurality of immovable areas, it is preferable to use a database or the like that holds a combination set in advance. FIG. 21 is a diagram for explaining an example of determination of one or more combinations of a plurality of pattern information. As shown in this figure, pattern information of “http://xxx.com” and “password: 123xxx456” was extracted from the stationary area A1 and the stationary area A2, respectively. Here, by referring to the database, it is determined that the character string “http” and the character string “password” are determined as pattern information to be combined. On the other hand, when the character strings “homepage address” and “zip code” are extracted from the non-moving area A1 and the non-moving area A2, respectively, they are determined not to be combined from the database, and thus are not combined.

  FIG. 15 is a diagram for explaining an example of pattern information acquisition when there are a plurality of spatially immovable regions. As shown in this figure, the pattern information for the immovable area A and the immovable area B extracted with certain moving image frame information is “〒 111-xxx” and “address: Tokyo ○ × ward ×× 4−4”. The text information “5” was extracted. Here, it can be determined from the database of FIG. Therefore, it is possible to obtain pattern information such as “〒 〒 111-xxx address: Tokyo xx ward xx4-5” by combining both. Of course, a combination of pattern information extracted from different immovable regions in both time and space may be performed.

    <Processing Flow of Third Embodiment> FIGS. 16A and 16B are flowcharts showing an example of a processing flow in the moving picture frame analysis apparatus of the present embodiment. As shown in (a) of this figure, it is first determined whether or not there has been a process start command (step S1601a). If there is a start command, moving image frame information is acquired, and it is determined whether a predetermined number of moving image frame information has been obtained (step S1602a). If the predetermined number has not been acquired, the moving image frame information acquisition process is performed again. On the other hand, if it is determined that a predetermined number of moving image frame information has been acquired, a plurality of immovable areas are detected from the acquired plurality of moving image frame information (step S1603a). Subsequently, a plurality of pattern information is extracted from the video information indicated in each detected immovable region (step S1604a). Finally, pattern information based on one or more combinations of the plurality of pattern information is acquired (step S1605a).

  Alternatively, as an example of another processing flow, as shown in FIG. 16B, first, it is determined whether or not there is a processing start command (step S1601b). If there is a start command, a plurality of pieces of moving picture frame information are acquired (step S1602b). Subsequently, it is determined whether or not a plurality of immovable areas are detected in the obtained plurality of moving image frame information (step S1603b). If it is determined in step S1603b that a plurality of immovable areas are detected, a plurality of pattern information is extracted from the video information indicated in each detected immovable area (step S1604b). Finally, pattern information obtained by one or more combinations of a plurality of pattern information is acquired (step S1605b). On the other hand, if it is determined in step S1603b that a non-moving area has not been detected, a plurality of pieces of moving image frame information acquisition in step S1602b are started again.

    <Simple Explanation of Effects of Third Embodiment> As described above, the moving picture frame analyzing apparatus according to the present embodiment can extract pattern information included in a plurality of immovable regions in time or / and space in combination. It becomes possible.

  << Embodiment 4 >> <Concept of Embodiment 4> FIG. 17 is a diagram for explaining an example of a concept of a moving picture frame analysis apparatus according to the present embodiment. As shown in this figure, first, the moving picture frame analysis device of the present embodiment extracts the information of the earthquake early warning as the pattern information from the moving picture image based on the moving picture frame analysis device of the second embodiment. At that time, the moving picture frame analysis apparatus according to the present embodiment acquires, for example, time information included in moving picture frame information that is a digital broadcast wave as a feature point, and broadcasts news at that time with reference to program guide information and the like. It is possible to control the tuner to match the radio reception of the broadcasting station. As described above, the moving image frame information analysis apparatus according to the present embodiment can perform the execution process in consideration of digital data such as time information included in the moving image frame information.

    <Configuration of Embodiment 4> FIG. 18 is a diagram illustrating an example of functional blocks in the moving picture frame analysis apparatus of the present embodiment. As shown in this figure, the “moving picture frame analyzing apparatus” (1800) of the present embodiment is based on the second embodiment, and includes a “moving picture frame information acquiring unit” (1801) and a “non-moving region detecting unit” (1802). A “pattern information extraction unit” (1803), a “pattern-specific execution process identifier holding unit” (1804), and an “execution process identifier acquisition unit” (1805). The moving picture frame analysis apparatus according to the present embodiment further includes a “digital data acquisition unit” (1806) and a “second execution process identifier holding unit” (1807) as feature points. The “moving frame information acquisition unit”, “non-moving region detection unit”, “pattern information extraction unit”, “per-pattern execution processing identifier holding unit”, and “execution processing identifier acquisition unit” are the same as those in the first and second embodiments. Since it has already been explained in the explanation, explanation here is omitted.

  The “digital data acquisition unit” (1806) has a function of acquiring digital data. “Digital data” is information included in the broadcast when the video frame information is information obtained by broadcasting. For example, information indicating the time, explanation information of the moving image included as the data broadcast, and the like can be given. It is done.

  The “second execution process identifier holding unit” (1807) associates the digital data acquired by the digital data acquisition unit (1806) with the execution process identifier acquired by the execution process identifier acquisition unit (1805). It has a function of holding a second execution process identifier. FIG. 20 is a diagram for explaining an example of the association of digital data, an execution process identifier, and a second execution process identifier. As shown in this figure, for example, the second execution indicating the time information as digital data and the TV reception software activation identifier as the execution process identifier, and the channel adjustment to the news program as the process to be executed accordingly. A process identifier is associated. Thereby, for example, when earthquake early warning is extracted as pattern information and the television is automatically started, the channel can be automatically adjusted to the news program. Alternatively, the execution process with the second execution process identifier may not be channel matching, but may be a startup of a sub-screen tuned to the corresponding channel.

  Alternatively, the program being broadcast is hot spring inn information, and the address of the homepage for reservation of the hot spring inn is extracted as pattern information from the video frame information. Then, the processing identifier for performing a route search is held as the second execution processing identifier in association with the execution processing identifier for displaying the hot spring inn information, which is digital data, and the accommodation reservation page on the Web browser. This also makes it possible to perform route search automatically.

    <Process Flow of Embodiment 4> FIGS. 19A and 19B are flowcharts showing an example of the process flow in the moving picture frame analyzing apparatus of the present embodiment. As shown in (a) of this figure, first, it is determined whether or not there is a processing start command (step S1901a). If there is a start command, moving image frame information is acquired, and it is determined whether a predetermined number of moving image frame information has been obtained (step S1902a). If the predetermined number has not been acquired, the moving image frame information acquisition process is performed again. On the other hand, if it is determined that a predetermined number of moving picture frame information has been acquired, a non-moving area is detected from the acquired moving picture frame information (step S1903a). Next, from the video information indicated in the detected non-moving area. Pattern information is extracted (step S1904a). Subsequently, the execution process identifier associated with the pattern information extracted in step S1904a is acquired from the execution process identifier previously stored in association with predetermined pattern information (step S1905a). Also, digital data is acquired (step S1906a). Finally, the second execution process identifier stored in advance in association with the digital data and the execution process identifier is associated with the execution process identifier acquired in step S1905a and the digital data acquired in step S1906a. A second execution process identifier is acquired (step S1907a).

  Alternatively, as an example of the flow of other processing, as shown in FIG. 19B, it is first determined whether or not there is a processing start command (step S1901b). If there is a start command, a plurality of pieces of moving picture frame information are acquired (step S1902b). Subsequently, it is determined whether or not a non-moving area is detected in the acquired plurality of moving image frame information (step S1903b). If it is determined in step S1903b that a non-moving area has been detected, pattern information is extracted from the video information indicated in the detected non-moving area (step S1904b). Next, the execution process identifier associated with the pattern information extracted in step S1904b is acquired from the execution process identifier stored in advance in association with predetermined pattern information (step S1905b). On the other hand, if it is determined in step S1103b that a non-moving region has not been detected, a plurality of moving image frame information acquisitions in step S1102b is started again. Also, digital data is acquired (step S1906b). Finally, the second execution process identifier stored in advance in association with the digital data and the execution process identifier is associated with the execution process identifier acquired in step S1905b and the digital data acquired in step S1906b. A second execution process identifier is acquired (step S1907b).

    <Simple Explanation of Effects of Embodiment 4> As described above, the moving image frame analysis apparatus of the present embodiment automatically performs processing such as application activation in consideration of digital data included in the digital broadcast wave. Is possible.

The figure for demonstrating an example of the concept of the moving image frame analyzer in Example 1. FIG. The figure showing an example of the functional block in the moving image frame information analysis apparatus of Example 1. The figure for demonstrating an example of the flame | frame displayed by the moving image frame information acquired in the moving image frame information acquisition part of the moving image frame information analysis apparatus of Example 1. FIG. The figure for demonstrating an example of the detection of the fixed area | region in the fixed area | region detection part of the moving image frame information analysis apparatus of Example 1. FIG. The figure for demonstrating an example of the extraction of the pattern information using the algorithm of an optical character reader in the pattern information extraction part of the moving image frame information analysis apparatus of Example 1 The figure for demonstrating another example of the extraction of the pattern information in the pattern information extraction part of the moving image frame information analysis apparatus of Example 1 7 is a flowchart illustrating an example of a process flow in the moving image frame information analysis apparatus according to the first embodiment. The figure for demonstrating an example of the concept of the moving image frame analyzer in Example 2. FIG. The figure showing an example of the functional block in the moving image frame information analysis apparatus of Example 2. The figure for demonstrating the correlation with the pattern information in the execution process identifier holding part classified by pattern of the moving image frame information analysis apparatus of Example 2, and an execution process identifier 7 is a flowchart illustrating an example of a processing flow in the moving image frame information analysis apparatus according to the second embodiment. The figure for demonstrating an example of the concept of the moving image frame analyzer in Example 3. FIG. The figure showing an example of the functional block in the moving image frame information analysis apparatus of Example 3. The figure for demonstrating an example of acquisition of the pattern information in case the multiple area | region pattern information acquisition means of the moving image frame information analysis apparatus of Example 3 has a plurality of non-moving areas in time. The figure for demonstrating an example of acquisition of the pattern information in case the multiple area | region pattern information acquisition means of the moving image frame information analysis apparatus of Example 3 has two or more immovable area | regions spatially. 10 is a flowchart illustrating an example of a processing flow in the moving image frame information analysis apparatus according to the third embodiment. The figure for demonstrating an example of the concept of the moving image frame analyzer in Example 4. FIG. The figure showing an example of the functional block in the moving image frame information analysis apparatus of Example 4. 10 is a flowchart illustrating an example of a processing flow in the moving image frame information analysis apparatus according to the fourth embodiment. The figure for demonstrating an example of correlation with the 2nd execution process identifier and the digital data and the execution process identifier in the 2nd execution process identifier holding | maintenance part of the moving image frame information analysis apparatus of Example 4 The figure for demonstrating an example of the judgment of the combination in the multiple area | region pattern information acquisition means of the moving image frame information analysis apparatus of Example 3. FIG.

Explanation of symbols

0200 Moving picture frame information analysis device 0201 Moving picture frame information acquisition unit 0202 Non-moving region detection unit 0203 Pattern information extraction unit 0904 Execution processing identifier holding unit by pattern 0905 Execution processing identifier acquisition unit 1806 Digital data acquisition unit 1807 Second execution processing identifier holding unit

Claims (9)

A video frame information acquisition unit for acquiring a plurality of video frame information;
A non-moving region detection unit that detects a non-moving region that is a region with less movement among the plurality of moving image frame information;
A pattern information extracting unit that extracts pattern information from video information indicated in the immovable region detected by the immovable region detecting unit;
A moving picture frame information analyzing apparatus. A pattern-specific execution process identifier holding unit that holds predetermined pattern information and an execution process identifier in association with each other;
An execution process identifier acquisition unit that acquires an execution process identifier associated with the pattern information extracted by the pattern information extraction unit from the pattern-specific execution process identifier holding unit;
The moving picture frame information analysis apparatus according to claim 1, comprising:   When there are a plurality of immovable areas detected by the immovable area detecting section, the pattern information extracting unit extracts pattern information from each immovable area and obtains pattern information based on one or more combinations thereof. The moving image frame information analysis apparatus according to claim 1, further comprising a plurality of area pattern information acquisition means. The video frame information is information obtained by broadcasting, and further includes a digital data acquisition unit that acquires the digital data when digital data information attached to the broadcasting is included,
Second execution process identifier holding for holding a second execution process identifier for identifying a process to be executed in association with the digital data acquired by the digital data acquisition unit and the execution process identifier acquired by the execution process identifier acquisition unit The moving image frame information analysis device according to claim 2, further comprising a unit.   5. The moving picture frame information analysis apparatus according to claim 1, wherein the pattern information is text information.   5. The moving image frame information analysis apparatus according to claim 1, wherein the pattern information is barcode information.   5. The moving image frame information analysis apparatus according to claim 1, wherein the pattern information is image information. A video frame information acquisition step for acquiring a plurality of video frame information;
A non-moving region detecting step for detecting a non-moving region that is a region with less motion among the plurality of moving image frame information acquired in the moving image frame information acquiring step;
A pattern information extracting step for extracting pattern information from the video information shown in the immovable area detected by the immovable area detecting step;
A method for analyzing moving picture frame information. A video frame information acquisition step for acquiring a plurality of video frame information;
A non-moving region detecting step for detecting a non-moving region that is a region with less motion among the plurality of moving image frame information acquired in the moving image frame information acquiring step;
A pattern information extracting step for extracting pattern information from the video information shown in the immovable area detected by the immovable area detecting step;
An execution process identifier acquiring step for acquiring an execution process identifier associated with the pattern information extracted in the pattern information extraction step from an execution process identifier stored in advance in association with predetermined pattern information;
A method for analyzing moving picture frame information.

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