Patent Publication Number: US-8996983-B2

Title: Device and a method for annotating content

Description:
FIELD OF THE INVENTION 
     The invention relates to a device for annotating content. 
     The invention further relates to a method for annotating content. 
     The invention further relates to a program element. 
     The invention further relates to a computer-readable medium. 
     BACKGROUND OF THE INVENTION 
     There is a trend of increasing electronics miniaturization, leading to the development of devices that may have more processing power, allowing them to become smarter. Furthermore, the trend of further technology integration will allow devices to integrate more and more technologies such as wireless networking and sensor capabilities into affordable products. The combination of these two trends will allow devices to become smart device, context aware and intelligently interacting with other such devices in a network (ad-hoc, fixed or otherwise). Such devices can be portable as well as stationary devices. Portable and stationary device makers tend to differentiate their device products, in both form and function, from other such products in the market. This will leave the user with even more such devices at home and on-the-move. 
     One use of such powerful devices is for the storage and/or rendering of personal content. In using such devices metadata of personal content, such as own created photos and videos, is important to users to be able to, for instance, easily organize, browse and find back their content. To manually annotate such content is a very laborious task for users. This is especially so since the amount of content produced, both commercially and personally, is ever increasing. Therefore, it is becoming virtually impossible to properly annotate all newly created content. Solutions are required that alleviate the users from such arduous tasks and enable them to start enjoying the content. 
     Whilst a lot of solutions, using content analysis or otherwise, are being developed for the purpose of helping the user to annotate content automatically. None are satisfactory. When considering personal content the following types of metadata are generally found to be important: 
     Why was the content created? What is the “event”, e.g. Summer holidays 
     Who appears in the created picture or video? E.g. my wife 
     When was the content created? E.g. July, Summer 
     Where was the content created? E.g. In Italy 
     Further, types of metadata related to concepts and object present in the content, such as “happy”, “beach” and “tree” can also be of importance to the user. 
     Concerning the recognition of who appears in photos and videos a lot of literature is available; see for instance Marc Davis, Michael Smith, John Canny, Nathan Good, Simon King, and Rajkumar Janakiraman, “Towards Context-Aware Face Recognition,” Proceedings of 13th Annual ACM International Conference on Multimedia (MM 2005) in Singapore, ACM Press, 483-486, 2005. This article specifically targets context-aware face recognition in personal photos created using mobile phones. A further example is provided in Ara V. Nefian, Monson H. Hayes III, 1999, “Face recognition using an Embedded HMM”, which is a face recognition method. 
     To determine where a content item was created, at creation time, it is widely known that a Global Positioning System (GPS) can be used. Further, there are also systems developed that try to analyse the content created, to infer where the place is captured by the content. For instance, in Risto Sarvas, Erick Herrarte, Anita Wilhelm, and Marc Davis, “Metadata Creation System for Mobile Images,” Proceedings of the Second International Conference on Mobile Systems, Applications, and Services (MobiSys2004) in Boston, Mass., ACM Press, 36-48, 2004, a created image may be uploaded to a server to be compared with other images. From such an analysis it can be derived, for instance, that an image was taken at the “Campanile” tower on the UC Berkeley campus, USA. 
     Furthermore, there also many efforts to detect concepts and objects, see for instance, Erik Murphy-Chutorianl, Sarah Aboutalib, Jochen Triesch, “Analysis of a Biologically-Inspired System for Real-time Object Recognition”, Cognitive Science Online, Vol. 3.2, pp. 1-14, 2005 and I. Cohen, N. Sebe, A. Garg, M. S. Lew, T. S. Huang, “Facial Expression Recognition from Video Sequences”, IEEE International Conference on Multimedia and Expo (ICME&#39;02), vol II, pp. 121-124, Lausanne, Switzerland, August 2002. 
     However, even given all of the work being done in content analysis it has been found that content analysis cannot provide 100% accurate annotation results. Whilst there are also efforts to incorporate user feedback and learning algorithms it remains an issue that a user will be required to provide significant amounts of feedback. 
     The inventors recognising this problem devised the present invention. 
     BRIEF SUMMARY OF THE INVENTION 
     The present invention seeks to improve the quality of annotation of content. 
     Accordingly, there is provided, in a first aspect of the present invention, a device for annotating content, the device comprising a means to analyse the content and generate a first output based upon the analysis of the content, a means to generate an annotation request, a means to communicate, the means to communicate being adapted to distribute the annotation request to at least one other device and to receive an annotation result from the at least one other device and a means to combine the first output and the annotation result to provide an improved output. 
     The device may analyse the content locally using a content analyser, however, the results will, of course, be no better than the best algorithms available. However, by requesting at least one further device to also perform content analysis, a second independent annotation result is determined. By combining the results of content analysis performed locally on the device with the independent results of content analysis performed and returned by at least one further device the individual and independent results may be combined to provide a combined and improved output. 
     According to a second aspect of the invention a method for annotating content is provided, the method comprising the method steps of analysing the content and generating a first output based upon the analysis of the content, generating an annotation request, communicating the annotation request to at least one other device and receiving an annotation result from the at least one other device and combining the first output and the annotation result to provide an improved output. 
     According to a third aspect of the invention a system for annotating content is provided, the system comprising a plurality of devices for annotating content, each device of the plurality of devices comprising a means to analyse the content and generate a first output based upon the analysis of the content, a means to generate an annotation request, a means to communicate, the means to communicate being adapted to distribute the annotation request to at least one other device and to receive an annotation result from the at least one other device and a means to combine the first output and the annotation result to provide an improved output. 
     According to a fourth aspect of the invention a program element directly loadable into the memory of a programmable device is provided, comprising software code portions for performing, when said program element is run on the device, the method steps of analysing content to be annotated and generating a first output based upon the analysis of the content, generating an annotation request, communicating the annotation request to at least one other device and receiving an annotation result from the at least one other device and combining the first output and the annotation result to provide an improved output. 
     According to a fifth aspect of the invention a computer-readable medium directly loadable into the memory of a programmable device is provided, comprising software code portions for performing, when said code portions are run on the device, the method steps of analysing content to be annotated and generating a first output based upon the analysis of the content, generating an annotation request, communicating the annotation request to at least one other device and receiving an annotation result from the at least one other device and combining the first output and the annotation result to provide an improved output. 
     In one embodiment a user interface may be provided, the user interface may be adapted to present the annotation request to a user and to receive feedback on the annotation request from the user and a means to combine further combines the feedback from the user to provide the improved output. This provides a fall back scenario for situations when the improvement in the quality of the annotation provided by the improved output is still not judged to be sufficient. 
     In a further embodiment a means to communicate may be adapted to receive external annotation requests from a further device and to transmit the feedback from the user to the further device. This provides a device to offer a service to further devices in a network to request and provide user feedback even though the further devices may not have suitable user interface capabilities to request feedback from the user themselves. 
     In another embodiment an annotation centre manager may be provided, the annotation centre manager may comprise a queue comprising a plurality of outstanding annotation requests for the user and a means to select a selected outstanding annotation request from the queue of outstanding annotation requests wherein the annotation centre manager is communicatively coupled to a user interface to communicate the selected outstanding annotation request to the user interface and to receive the feedback from the user interface. This allows annotation requests to be collected and presented to a user at a suitable moment. 
     In yet another embodiment an annotation centre manager may further comprise a means to determine obsolete outstanding annotation requests which are outstanding annotation requests made obsolete by the feedback from the user and a means to delete the obsolete outstanding annotation requests from the queue and wherein a means to communicate is further adapted to communicate the feedback to originators of the obsolete outstanding annotation requests. This allows annotation requests that were queued to be analysed taking into account the feedback from the user and annotation requests which may have become obsolete based on the feedback from the user may be removed from the queue and communicated back to the originator of the obsolete annotation requests. This also reduces the amount of user interaction required, by removing the need to answer obsolete annotation requests. 
     In an embodiment a means to communicate may be further adapted to receive a message identifying a further device as an annotation centre manager, transmit external annotation requests to the annotation centre manager identified and to receive external feedback from a user from the annotation centre manager identified and a means to combine may further combine the external feedback from the user to provide the improved output. This allows a further device to present and receive user feedback on behalf of the device and this is useful when the further device has more powerful user interface capabilities. 
     In another embodiment a means to detect that the user is in the vicinity of the device may be provided along with a means to identify the device as an annotation centre manager in a network of devices based upon detection that the user is in the vicinity of the device and a means to communicate may be further adapted to receive external annotation requests from the network of devices. This allows annotation requests to be directed to a local device to the user. This also allows feedback to be gathered from the user in a fast and efficient manner. 
     In another embodiment a means for storing the improved output may be provided. Storing the improved output allows the metadata relating to the content to be permanently of an improved quality. 
     In a further embodiment a means to combine may further comprise a confidence level determination unit, the confidence level determination unit may be adapted to determine a first confidence level of the first output, the first confidence level indicating the confidence that the first output is correct, determine a second confidence level of the annotation result, the second confidence level indicating the confidence that the annotation result is correct and wherein a means to combine may be adapted to further combine the first output and the annotation result to provide an improved output based upon the first confidence level and the second confidence level. This allows a confidence level to be determined for each result of content analysis, even in situation wherein the content analysis algorithm cannot provide a confidence level itself. 
     In a further embodiment a device according to the invention may be realized as at least one of the group consisting of a Set-Top-Box device, a digital video recording device, a network-enabled device, a conditional access system, a portable audio player, a portable video player, a mobile phone, a DVD player, a CD player, a hard disk based media player, an Internet radio device, a computer, a television, a public entertainment device, a memory stick and an MP3 player. However, these applications are only exemplary. 
     In another embodiment an annotation request may be presented to a user and feedback on the annotation request may be received from the user and a method step of combining may further combine the feedback from the user to provide the improved output. This provides a fall back scenario for situations when the improvement in the quality of the annotation provided by the improved output is still not judged to be sufficient. 
     In an embodiment external annotation requests may be received from a further device and feedback from the user may be transmitted to the further device. This provides a service to further devices in a network to request and provide user feedback even though the further devices may not have suitable user interface capabilities to request feedback from the user themselves. 
     The data processing required according to the invention can be realized by a computer program, that is to say by software, or by using one or more special electronic optimization circuits, that is to say in hardware, or in hybrid form, that is to say by means of software components and hardware components. The data processing may also be provided by an external service running on a server. 
     The aspects defined above and further aspects of the invention are apparent from the examples of embodiment to be described hereinafter and are explained with reference to these examples of embodiment. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The invention will be described in more detail hereinafter with reference to examples of embodiment but to which the invention is not limited. 
         FIG. 1  illustrates a system diagram of a device according to an embodiment of the invention; 
         FIG. 2  illustrates in more detail a device according to an embodiment of the invention; 
         FIG. 3  illustrates in an embodiment of the invention wherein a confidence level in the results of the content analysis is determined; 
         FIG. 4  illustrates in an embodiment of the invention wherein feedback from a user is requested based upon a confidence level in the results of the content analysis; 
         FIG. 5  illustrates in an embodiment of the invention wherein annotation is requested from a further device based upon a confidence level in the results of the content analysis; 
         FIG. 6  illustrates in an embodiment of the invention wherein annotation requests are queued and obsolete annotation requests may be deleted from the queue based upon feedback from a user; 
         FIG. 7  illustrates in an embodiment of the invention wherein the proximity of a user to the device is detected such that the device may inform further devices that it may receive annotation requests requiring feedback from a user; 
         FIG. 8  illustrates a flowchart used in an embodiment of the invention; 
         FIG. 9  illustrates a second flowchart used in an embodiment of the invention; and 
         FIG. 10  illustrates a third flowchart used in an embodiment of the invention. 
     
    
    
     The Figures are schematically drawn and not true to scale, and the identical reference numerals in different Figures refer to corresponding elements. It will be clear for those skilled in the art, that alternative but equivalent embodiments of the invention are possible without deviating from the true inventive concept, and that the scope of the invention will be limited by the claims only. 
     DETAILED DESCRIPTION OF THE INVENTION 
       FIG. 1  illustrates an embodiment of the invention. A device  100  is provided which may reside in a network  180 . The network  180  may be a locale network or the Internet. A further device  165  may also reside in the network. The device  100  may be an autonomous device, enabling device  100  to work without explicit control of other devices and to control who or what is accessing and using the functionality and data of the device  100 . This is of special importance to portable devices that need to work in different environments, some of which may be outside the users own (home/private) network. The device  100  may comprise a processor  120  for executing machine-readable code as is commonly applied in present day devices. The device  100  may also comprise a bus  140  for interconnecting system components within the device  100 . For example, the processor  120  may use a memory  110  to run code and/or store data. The device may also comprise a means to communicate, such as network interface  130 , allowing the device  100  to communicate with the further device  165  or other devices. 
     The network interface  130  may be a network interface such as a wired Ethernet interface or it may also be wireless in nature. For example, the network interface  130  may be a WiFi, Bluetooth, mobile phone or other suitable network interface. A display  160  may be provided for rendering content to a user  192 . The user  192  may interact with the device  100  suing a remote control  191  and a user interface  190 . The user interface  190  may of course also make use of the display  160 . Other forms of user interaction, beyond a remote control may also be suitable, such as a keyboard, a touch screen, a mouse or other point device. A storage means  170  may also be provided for storing content, metadata and intermediate and/or final results of any processing steps. The storage means may be volatile or non-volatile and may be for example, SRAM, DRAM or FLASH memory, a hard disk drive or an optical drive. It is to be noted the content may be accessed from the storage means  170 , but equally possible is that the content be accessed via the network interface  130 . In such a case the storage means  170  is entirely optional. 
     A content analyser  150  may be provided to analyse content accessible by the device, either locally or via the network  180 . Analysis of the content may provide more metadata or metadata of an improved quality. This is especially relevant when considering personal content where the following types of metadata are generally found to be important: 
     Why was the content created? What is the “event”, e.g. Summer holidays 
     Who appears in the created picture or video ? E.g. my wife 
     When was the content created? E.g. July, Summer 
     Where was the content created? E.g. In Italy 
     The user  192  also values metadata relating to higher-level concepts and objects contained within the content, for example, the concepts of “happy”, “beach” and “tree” have been found to be of importance to the user. As already noted when concerning the recognition of who appears in photos and videos a lot of literature is available. For example, “Towards Context-Aware Face Recognition,” Proceedings of 13th Annual ACM International Conference on Multimedia (MM 2005) in Singapore, ACM Press, 483-486, 2005 specifically targets context-aware face recognition in personal photos created using mobile phones. A further example is provided in Ara V. Nefian, Monson H. Hayes III, 1999, “Face recognition using an Embedded HMM”, which is a face recognition method. 
     Other important metadata aspects are related to determining where a content item was created, at creation time, it is widely known that a Global Positioning System (GPS) can be used. Further, there are also systems developed that try to analyse the content created, to infer where the place is captured by the content. For instance, in “Metadata Creation System for Mobile Images,” Proceedings of the Second International Conference on Mobile Systems, Applications, and Services (MobiSys2004) in Boston, Mass., ACM Press, 36-48, 2004, a created image may be uploaded to a server to be compared with other images. From such an analysis it can be derived, for instance, that an image was taken at the “Campanile” tower on the UC Berkeley campus, USA. 
     Furthermore, there also many efforts to detect concepts and objects, see for instance, Erik Murphy-Chutorianl, Sarah Aboutalib, Jochen Triesch, “Analysis of a Biologically-Inspired System for Real-time Object Recognition”, Cognitive Science Online, Vol. 3.2, pp. 1-14, 2005 and I. Cohen, N. Sebe, A. Garg, M. S. Lew, T. S. Huang, “Facial Expression Recognition from Video Sequences”, IEEE International Conference on Multimedia and Expo (ICME&#39;02), vol II, pp. 121-124, Lausanne, Switzerland, August 2002. 
     All of these forms of content analysis are useful, however, they are not reliable enough to work on their own. Therefore there are also efforts to incorporate user feedback. This feedback can be used to make annotations where the content analysis method results have low confidence and to improve the content analysis algorithms (online learning). For example, the “Semantic Learning and Analysis of Multimedia”, SLAM project, IBM Research, http://www.research.ibm.com/slam/. The known solutions mostly focus on how to use feedback for online learning of content analysis algorithms. 
     A completely different way for users to get their content annotated is through “collaborative tagging”, for example in Scott A. Golder and Bernardo A. Huberman, “The Structure of Collaborative Tagging Systems”, to appear in the Journal of Information Science (2006), Information Dynamics Lab, HP Labs. In this solution users may add annotations to any content uploaded to a website. 
     In the following annotation means not only the creation of metadata but also the creation of user added information. Annotations may be optionally be stored to assist in future browsing or search actions. 
     It remains the case that user feedback is only reliable for the explicit questions posed to a user and any inferences taken from responses of a user will not be completely reliable. Furthermore, due to the wide variety of processing platforms, i.e. devices, and varying capabilities of devices the extent to which the results of any single content analysis algorithm can be trusted will be limited. 
     In  FIG. 2  an embodiment is shown in more detail that improves the quality of output from content analysis. Content  210  to be annotated is made available to the device  100 . The content  210  may be photos, audio, video or some other data form. The content analyser  150  analyses the content  210  using a known algorithm, for example, face detecting algorithm. The content analyser  150  generates a first output  205  with the results of the content analysis step. The first output  205  may comprise only annotations or annotations and a measure of the confidence in the annotations. The actual annotations and any measure of the confidence are specific to each any every content analysis algorithm, so some form of standardisation of, especially, the measure of the confidence may be useful. The first output  205  may comprise, for example, the number of faces, who the faces represent, etc. Many other content analysis algorithms are also possible that focus on video features, such as colour etc, or audio features, such as volume, tempo etc. 
     The first output  205  is communicated to an annotation manager  220 . The annotation manager  220  may comprises an annotation request generator  230  and a combiner  240 . The annotation request generator  230  receives the first output  205  and generates an annotation request  215  based upon the first output  205 . Optionally, the annotation request generator  230  may only provide a link to the content  210  in the annotation request  215  such that the further device  165  may analyse the content  210  from scratch. The annotation request  215  is communicated internally to the network interface  130 , from where it is distributed within the network  180  to other devices, such as, further device  165 . 
     In this example, the further device  165  analyses the content  210  according to the annotation request  215 . The annotation request  215  may be a general request to analyse the content  210  from scratch, or it may be a specific request to analyses a certain aspect of the content  210 . For example, a specific request may a request to analyse only the faces detected in a photo. After performing the analysis, the further device  165  will reply to the annotation request  215  with an annotation result  225 . The independent annotation result may be performed by a different content analysis algorithm or be analysed based upon different background knowledge. The annotation result  225  may comprise only the annotation metadata or optionally also a measure of the confidence in the annotation metadata. 
     The device  100  receives the annotation result  225  from the further device  165  via the network interface  130 . The combiner  240  receives the annotation result  225  and combines it with the first output  205 . The combiner  240  analyses the two independent results and judges the quality or confidence in one or both results to provide an improved output  235 . The improved output  235  may be any known combination or function of the first output  205  and the annotation result  225 . 
     In another embodiment as shown in  FIG. 3  the annotation manager  220  may comprise a confidence level determination unit  310 . The confidence level determination unit  310  is shown to intercept the first output  205  from the content analyser  150 . For clarity it is noted that the content analyser  150  may be a hardware component or a software module running on processor  120 . If the content analyser  150  does not provide any measure of confidence in the first output  205 , the confidence level determination unit  310  may estimate the confidence level using historical information. Based upon the level of confidence in the first output  205  the confidence level determination unit  310  may decide to trigger the annotation request generator  230  to generate the annotation request  215  or pass the first output  205  directly to the improved output  235  via switch  320 . Should the path be chosen making use of the annotation request  215  then the annotation request  215  may be processed normally and communicated to the improved output  235  via the combiner  240  and switch  320 , when set in the lower position. 
     In  FIG. 4  a further embodiment is shown. In  FIG. 4  the annotation manager  220  may comprise an annotation request receiver  410  capable of receiving annotation requests  215  from devices on the network  180 . The annotation request receiver  410  may be capable of initiating the content analysis of the content  210 , using the content analyser  150 . The content  210  may be remotely located, as shown in  FIG. 4 . The content  210  may also be stored on the further device  165 . The annotation manager  220  may further comprise an annotation question generator  420 . The annotation question generator  420  may be communicatively coupled to the confidence level determination unit  310  and be triggered by the result of the analysis performed by the confidence level determination unit  310  to generate a question for the user  192 . The display  160  and the user interface  190  may be used for this purpose. The user  192  may provide feedback  415 . Based upon the feedback  415  the annotation question generator  420  generates an annotation result  225  of a high confidence level. The annotation result  225  may be communicated back to an originator of the annotation request  225 . This communication may be performed by the network interface  130 , though this is not shown in  FIG. 4 . 
     In  FIG. 5  an embodiment is shown wherein an annotation question may be communicated via network interface  130  to a remote device  510  comprising an annotation centre manager  520 . The annotation centre manager  520  displays the annotation question to the user in a similar manner as described in  FIG. 4 . The feedback  415  is communicated from the annotation centre manager  520  of the remote device  510  via the network  180  to the annotation question generator  420  of the device  100 . The annotation result  225  is then generated by the annotation question generator  420 . Again the annotation result  225  may be communicated to other devices via the network interface  130 . 
     In  FIG. 6  an embodiment is shown where device  100  may act as an annotation centre manager  520  in the network  180 . The annotation centre manager  520  may comprise an annotation request receiver  410  and an annotation request queue  620 . This allows annotation requests to be collected until the user  192  is ready to give feedback. The annotation request queue  620  may trigger the user interface  190  to directly request feedback from the user  192 . Alternatively, the annotation request queue  620  may trigger the content analyser  150  to analyse the content  210 . Based upon the feedback  415  from the user  192  an obsolete requests determination unit  630  may determine which requests in the annotation request queue  620  are now obsolete taking into account the feedback  415  provided by the user  192 . For example, if after the feedback  415  has been analysed that the face of “John” may now be recognised with a high confidence. Any other annotation requests relating to the face of “John” do not need to be forwarded to the user  192 . Therefore, the workload required from the user  192  is reduced. 
     In  FIG. 7  another embodiment of device  100  operating as an annotation centre manager  520  is shown. The annotation centre manager  520  may also comprise a user proximity detection unit  710 . The user proximity detection unit  710  may use any known means to detect that the user  192  is in close proximity to the device  100 . For example, the user proximity detection unit  710  may use a camera, a thermal detector etc. The user proximity detection unit  710  may also infer the proximity of the user  192  by noting user interaction and the time elapsed since such interaction occurred. For example, if the user  192  is operating, or has very recently operated, the device  100  then the user  192  will probably be within close proximity to the device  100 . The user proximity detection unit  710  may then inform other devices in the network  180 , via an indication  705 , that it should become the current central annotation centre manager and all annotation requests or questions requiring user feedback should be directed to device  100 . 
     In  FIG. 8  a flowchart is shown indicating a method for implementing an embodiment of the invention on the processor  120  of device  100 . In step  800  content  210  is received, or at least made accessible. In step  810  the content  210  is analysed locally using a content analysis algorithm and the first output  205  is produced. At step  820  annotation request  215  is generated and at step  830  the annotation request  215  is communicated to a further device  195 . At step  840  annotation result  225  is received from the further device  195 . At step  850  the first output  225  and the annotation result  225  are combined to provide an improved output  235 . 
     In  FIG. 9  a second flowchart is shown indicating a further method for implementing an embodiment of the invention on the processor  120  of device  100 . After step  820  two parallel paths are possible. The first path encompasses method steps as described in the text of  FIG. 8 , namely steps  830  and  840 . The second path presents the annotation request  215  as a question to the user  192  in step  910 . The presentation to the user  192  may be on a local device, for example, device  100 , or the further device  165 . The exact location of the user  192  is not of importance. It is however important that the user  192  provides the feedback  415  in step  920 . In step  930  the first output  205 , the annotation result  225  and the feedback  415  are all combined to provide a very high quality annotation as an improved output  235 . 
     In  FIG. 10  a third flowchart is shown indicating a further method for implementing an embodiment of the invention on the processor  120  of device  100 . In the embodiment of  FIG. 10  at step  1010  external annotation requests may be received from a remote device. Step  910  and step  920  are identical to those steps described in  FIG. 9 , but operate on the external annotation request. Again, the presentation to the user  192  may be on a local device, for example, device  100 , or the further device  165 . At step  1020  the feedback  415  may be transmitted back to the originator of the external annotation request. This allows annotation requests to be transferred to a location close to the user  192 . 
     In summary the invention discloses methods and devices for annotating content. The device may comprise a means to analyse the content and generate a first output based upon the analysis of the content, a means to generate an annotation request, a means to communicate, the means to communicate being adapted to distribute the annotation request to at least one other device and to receive an annotation result from the at least one other device and a means to combine the first output and the annotation result to provide an improved output. By combining multiple independent results of content analysis algorithms from different devices, possibly based upon background different knowledge a higher quality result is provided for the annotation. 
     It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be capable of designing many alternative embodiments without departing from the scope of the invention as defined by the appended claims. Furthermore, any of the embodiments described comprise implicit features, such as, an internal current supply, for example, a battery or an accumulator. In the claims, any reference signs placed in parentheses shall not be construed as limiting the claims. The word “comprising” and “comprises”, and the like, does not exclude the presence of elements or steps other than those listed in any claim or the specification as a whole. The singular reference of an element does not exclude the plural reference of such elements and vice-versa. In a device claim enumerating several means, several of these means may be embodied by one and the same item of hardware. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.