Abstract:
A parse module calibrates an interior space by parsing objects and words out of an image of the scene and comparing each parsed object with a plurality of stored objects. The parse module further selects a parsed object that is differentiated from the stored objects as the first object and stores the first object with a location description. A search module can detect the same objects from the scene and use them to determine the location of the scene.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This is a continuation application of and claims priority to U.S. patent application Ser. No. 13/107,072 entitled “INTERIOR LOCATION IDENTIFICATION” and filed on May 13, 2011 for James Billingham, which is incorporated herein by reference for all purposes. 
    
    
     BACKGROUND 
     1. Field 
     The subject matter disclosed herein relates to location identification and more particularly relates to interior location identification. 
     2. Description of the Related Art 
     Global Positioning System (GPS) devices are frequently used to determine a position and/or support navigation in exterior spaces. However, GPS signals often cannot be received in interior spaces such as inside of a building. As a result, a user may be unable to determine a location, use a navigation program, or use other location dependent functions of an electronic device. 
     BRIEF SUMMARY 
     From the foregoing discussion, it should be apparent that a need exists for a method that identifies interior locations. Beneficially, such a method would determine a location within an interior location such as a building or subway station. 
     The present invention has been developed in response to the present state of the art, and in particular, in response to the problems and needs in the art that have not yet been fully solved by currently available interior location identification methods. Accordingly, the present invention has been developed to provide a method for identifying interior locations that overcome many or all of the above-discussed shortcomings in the art. 
     A method of the present invention is presented for interior location identification. The method parses at least one object from a first image of an interior space and compares each parsed object with a plurality of stored objects. The method further selects a parsed object that is differentiated from the stored objects as the first object and indexes a location description of the interior space with the first object in a location record. 
     References throughout this specification to features, advantages, or similar language do not imply that all of the features and advantages may be realized in any single embodiment. Rather, language referring to the features and advantages is understood to mean that a specific feature, advantage, or characteristic is included in at least one embodiment. Thus, discussion of the features and advantages, and similar language, throughout this specification may, but do not necessarily, refer to the same embodiment. 
     Furthermore, the described features, advantages, and characteristics of the embodiments may be combined in any suitable manner. One skilled in the relevant art will recognize that the embodiments may be practiced without one or more of the specific features or advantages of a particular embodiment. In other instances, additional features and advantages may be recognized in certain embodiments that may not be present in all embodiments. 
     These features and advantages of the embodiments will become more fully apparent from the following description and appended claims, or may be learned by the practice of embodiments as set forth hereinafter. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       In order that the advantages of the embodiments of the invention will be readily understood, a more particular description of the embodiments briefly described above will be rendered by reference to specific embodiments that are illustrated in the appended drawings. Understanding that these drawings depict only some embodiments and are not therefore to be considered to be limiting of scope, the embodiments will be described and explained with additional specificity and detail through the use of the accompanying drawings, in which: 
         FIG. 1  is a perspective drawing illustrating one embodiment of an interior space; 
         FIG. 2  is a drawing illustrating one embodiment of an image; 
         FIG. 3  is a schematic block diagram illustrating one embodiment of a location record; 
         FIG. 4  is a schematic block diagram illustrating one embodiment of a data store; 
         FIG. 5  is a schematic block diagram illustrating one embodiment of a computer; 
         FIG. 6  is a schematic block diagram illustrating one embodiment of an interior location identification apparatus; 
         FIG. 7  is a schematic flow chart diagram illustrating one embodiment of an interior location storage method; and 
         FIG. 8  is a schematic flow chart diagram illustrating one embodiment of an interior location identification method. 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method, and/or computer program product. Accordingly, aspects of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a “circuit,” “module,” or “system.” Furthermore, aspects of the present invention may take the form of a computer program product embodied in one or more computer readable medium(s) having computer readable program code embodied thereon. 
     Many of the functional units described in this specification have been labeled as modules, in order to more particularly emphasize their implementation independence. For example, a module may be implemented as a hardware circuit comprising custom VLSI circuits or gate arrays, off-the-shelf semiconductors such as logic chips, transistors, or other discrete components. A module may also be implemented in programmable hardware devices such as field programmable gate arrays, programmable array logic, programmable logic devices or the like. 
     Modules may also be implemented in software for execution by various types of processors. An identified module of computer readable program code may, for instance, comprise one or more physical or logical blocks of computer instructions which may, for instance, be organized as an object, procedure, or function. Nevertheless, the executables of an identified module need not be physically located together, but may comprise disparate instructions stored in different locations which, when joined logically together, comprise the module and achieve the stated purpose for the module. 
     Indeed, a module of computer readable program code may be a single instruction, or many instructions, and may even be distributed over several different code segments, among different programs, and across several memory devices. Similarly, operational data may be identified and illustrated herein within modules, and may be embodied in any suitable form and organized within any suitable type of data structure. The operational data may be collected as a single data set, or may be distributed over different locations including over different storage devices, and may exist, at least partially, merely as electronic signals on a system or network. Where a module or portions of a module are implemented in software, the computer readable program code may be stored and/or propagated on in one or more computer readable medium(s). 
     The computer readable medium may be a tangible computer readable storage medium storing the computer readable program code. The computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, holographic, micromechanical, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. 
     More specific examples of the computer readable medium may include but are not limited to a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a portable compact disc read-only memory (CD-ROM), a digital versatile disc (DVD), an optical storage device, a magnetic storage device, a holographic storage medium, a micromechanical storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, and/or store computer readable program code for use by and/or in connection with an instruction execution system, apparatus, or device. 
     The computer readable medium may also be a computer readable signal medium. A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electrical, electro-magnetic, magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport computer readable program code for use by or in connection with an instruction execution system, apparatus, or device. Computer readable program code embodied on a computer readable signal medium may be transmitted using any appropriate medium, including but not limited to wireline, optical fiber, Radio Frequency (RF), or the like, or any suitable combination of the foregoing 
     In one embodiment, the computer readable medium may comprise a combination of one or more computer readable storage mediums and one or more computer readable signal mediums. For example, computer readable program code may be both propagated as an electro-magnetic signal through a fiber optic cable for execution by a processor and stored on RAM storage device for execution by the processor. 
     Computer readable program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++, PHP or the like and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The computer readable program code may execute entirely on the user&#39;s computer, partly on the user&#39;s computer, as a stand-alone software package, partly on the user&#39;s computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user&#39;s computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). 
     The computer program product may be shared, simultaneously serving multiple customers in a flexible, automated fashion. The computer program product may be standardized, requiring little customization and scalable, providing capacity on demand in a pay-as-you-go model. 
     The computer program product may be stored on a shared file system accessible from one or more servers. The computer program product may be executed via transactions that contain data and server processing requests that use Central Processor Unit (CPU) units on the accessed server. CPU units may be units of time such as minutes, seconds, hours on the central processor of the server. Additionally the accessed server may make requests of other servers that require CPU units. CPU units are an example that represents but one measurement of use. Other measurements of use include but are not limited to network bandwidth, memory usage, storage usage, packet transfers, complete transactions etc. 
     When multiple customers use the same computer program product, transactions are differentiated by the parameters included in the transactions that identify the unique customer and the type of service for that customer. All of the CPU units and other measurements of use that are used for the services for each customer are recorded. When the number of transactions to any one server reaches a number that begins to affect the performance of that server, other servers are accessed to increase the capacity and to share the workload. Likewise when other measurements of use such as network bandwidth, memory usage, storage usage, etc. approach a capacity so as to affect performance, additional network bandwidth, memory usage, storage etc. are added to share the workload. 
     The measurements of use used for each service and customer are sent to a collecting server that sums the measurements of use for each customer for each service that was processed anywhere in the network of servers that provide the shared execution of the computer program product. The summed measurements of use units are periodically multiplied by unit costs and the resulting total computer program product service costs are alternatively sent to the customer and or indicated on a web site accessed by the customer which then remits payment to the service provider. 
     In another embodiment, the service provider requests payment directly from a customer account at a banking or financial institution. 
     In another embodiment, if the service provider is also a customer of the customer that uses the computer program product, the payment owed to the service provider is reconciled to the payment owed by the service provider to minimize the transfer of payments. 
     Reference throughout this specification to “one embodiment,” “an embodiment,” or similar language means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. Thus, appearances of the phrases “in one embodiment,” “in an embodiment,” and similar language throughout this specification may, but do not necessarily, all refer to the same embodiment, but mean “one or more but not all embodiments” unless expressly specified otherwise. The terms “including,” “comprising,” “having,” and variations thereof mean “including but not limited to” unless expressly specified otherwise. An enumerated listing of items does not imply that any or all of the items are mutually exclusive and/or mutually inclusive, unless expressly specified otherwise. The terms “a,” “an,” and “the” also refer to “one or more” unless expressly specified otherwise. 
     Furthermore, the described features, structures, or characteristics of the embodiments may be combined in any suitable manner. In the following description, numerous specific details are provided, such as examples of programming, software modules, user selections, network transactions, database queries, database structures, hardware modules, hardware circuits, hardware chips, etc., to provide a thorough understanding of embodiments. One skilled in the relevant art will recognize, however, that embodiments may be practiced without one or more of the specific details, or with other methods, components, materials, and so forth. In other instances, well-known structures, materials, or operations are not shown or described in detail to avoid obscuring aspects of an embodiment. 
     Aspects of the embodiments are described below with reference to schematic flowchart diagrams and/or schematic block diagrams of methods, apparatuses, systems, and computer program products according to embodiments of the invention. It will be understood that each block of the schematic flowchart diagrams and/or schematic block diagrams, and combinations of blocks in the schematic flowchart diagrams and/or schematic block diagrams, can be implemented by computer readable program code. The computer readable program code may be provided to a processor of a general purpose computer, special purpose computer, sequencer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the schematic flowchart diagrams and/or schematic block diagrams block or blocks. 
     The computer readable program code may also be stored in a computer readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer readable medium produce an article of manufacture including instructions which implement the function/act specified in the schematic flowchart diagrams and/or schematic block diagrams block or blocks. 
     The computer readable program code may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the program code which executed on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. 
     The schematic flowchart diagrams and/or schematic block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of apparatuses, systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the schematic flowchart diagrams and/or schematic block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions of the program code for implementing the specified logical function(s). 
     It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the Figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. Other steps and methods may be conceived that are equivalent in function, logic, or effect to one or more blocks, or portions thereof, of the illustrated Figures. 
     Although various arrow types and line types may be employed in the flowchart and/or block diagrams, they are understood not to limit the scope of the corresponding embodiments. Indeed, some arrows or other connectors may be used to indicate only the logical flow of the depicted embodiment. For instance, an arrow may indicate a waiting or monitoring period of unspecified duration between enumerated steps of the depicted embodiment. It will also be noted that each block of the block diagrams and/or flowchart diagrams, and combinations of blocks in the block diagrams and/or flowchart diagrams, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer readable program code. 
       FIG. 1  is a perspective drawing illustrating one embodiment of an interior space  100 . The interior space  100  may be a room in a building. The interior space  100  is exemplary of the other interior spaces, including the interior of a shopping area, a transportation facility, an entertainment venue, a restaurant, an apartment or flat, a home, and the like. For simplicity the interior space  100  is described herein as being within a building. 
     The depicted interior space  100  includes a door  105 , a signal box  110 , one or more illustrations  115 ,  120 , a credenza a  130 , a vase  125 , and a wall  135 . In one embodiment, a camera  140  records a first image of the interior space  100 . The camera  140  may be a digital still camera, a digital video camera, or the like. The camera  140  may be embodied in a device such as a cellular telephone, a tablet, a notebook computer, or the like. In one embodiment, the first image comprises a plurality of images. The plurality of images may be digitally combined into a single image. Images may be a Motion Picture Experts Group (MPEG)-1 file, an MPEG-2 file, an MPEG-3 file, an MPEG-4 file, an MPEG-7 file, an MPEG-21 file, Portable Network Graphics (PNG) file, a Joint Photographic Experts Group (JPEG) file, a Graphics Interchange Format (GIF) file, or the like. 
       FIG. 2  is a front view drawing illustrating one embodiment of an image  200 . The image  200  may be the first image captured by the camera  140  as described in  FIG. 1 . In an alternate embodiment, the image  200  may be a second image that is subsequently captured as will be described hereafter. The description of the image  200  refers to elements of  FIG. 1 , like numbers referring to like elements. The image  200  includes the illustration  120 , the vase  125 , the credenza  130 , and the wall  135 . In the depicted embodiment, the illustration  120  includes text  205 . 
     In one embodiment, the one or more objects are parsed from the image  200 . For example, illustration  120 , the text  205 , the vase  125 , the credenza  130 , and the wall  135  may each be parsed as an object as will be described hereafter. 
       FIG. 3  is a schematic block diagram illustrating one embodiment of a location record  300 . The location record  300  may store an object parsed from the image  200  of  FIG. 2  as a first object  305 . The description of the location record  300  refers to elements of  FIGS. 1-2 , like numbers referring to like elements. The location record  300  includes the first object  305 , a room number  310 , an address  315 , a navigation direction  320 , a building map  325 , coordinates  345 , a secondary location indication  330 , a last GPS coordinate  335 , and an absolute position  340 . The object  305 , room number  310 , address  315 , navigation direction  320 , building map  325 , coordinates  345 , secondary location indication  330 , last GPS coordinate  335 , and absolute position  340  may be stored in data structures of the location record  300 . 
     The first object  305  may include one or more files storing one or more first objects  305 . In addition, the first object  305  may store one or more parsed characteristics of the first object  305 . The parsed characteristics may include but are not limited to color, shape, hue, a hash of an image, the Fourier transform of an image, vectors for one or more lines, and reflectivity values. The parsed characteristics may also include a spatial relationship between a plurality first objects  305 . For example, the spatial relationship may include a three-dimensional position of each first object  305 . Alternatively, the spatial relationship may include a two-dimensional position of each first object  305  on the image  200 . 
     The room number  310 , address  315 , navigation direction  320 , building map  325 , coordinates  345 , secondary location indication  330 , last GPS coordinate  335 , and absolute position  340  may be embodied in a location description  350 . The room number  310  may include a room number, a room description. The coordinates  345  may comprise two or more coordinates for a building map, coordinates within a building model, coordinates within a site grid, global coordinates, and the like. 
     The address  315  may include a street address for the interior space  100 . The navigation direction  320  may include one or more directions to the interior space  100  from one or more entrances of the building. The building map  325  may store the building map. The building map  325  may be a two-dimensional map of the building, one or more two-dimensional maps of each floor of the building, a three-dimensional model of the building, or the like. In one embodiment, the room coordinate stored in the room number  310  refers to a location on the building map  325 . The coordinates  345  may indicate a position on the building map  325 . 
     The secondary location indication  330  may be a least one of a wireless network identification, a cellular network identification, an infrared navigation beacon. The wireless network identification may be an identification for a WiFi network, a Bluetooth network, or the like. For example, the signal box  110  may be a transceiver for the WiFi network and/or the Bluetooth network. The wireless network may also be a plurality of broadcast stations including radio stations, television stations, and the like, a WiFi network, a Bluetooth network, communications in a specified radio frequency band, and the like. 
     The cellular telephone network identification may include an identification from one or more base transceiver identifications, one or more signal strengths, and/or one or more signal directions. The infrared navigation beacon may be an infrared signal broadcast by the signal box  110 . 
     The last GPS coordinate  335  may be a GPS coordinate recorded before a GPS signal is lost within the building. For example, the last GPS coordinate may be a position recorded by a cellular telephone that is carried in to the building prior to losing GPS signals. The absolute position  340  may be a coordinate, a street address, or the like. The absolute position  340  may be added to the location record  300  subsequent to creation of the location record  300 . 
     The location record  300  is indexed using the first object  305  so that the location description  350  may be retrieved by identifying the first object  305 . The room number  310 , address  315 , navigation direction  320 , building map  325 , coordinates  345 , secondary location indication  330 , last GPS coordinate  335 , and absolute position  340  may also be searchable, allowing the location record  300  to be identified using any data stored therein. 
       FIG. 4  is a schematic block diagram illustrating one embodiment of a data store  400 . The data store  400  may store a plurality of the location records  300  described in  FIG. 3 . The data store  400  may be stored on a computer readable medium such as a computer readable storage medium. 
       FIG. 5  is a schematic block diagram illustrating one embodiment of a computer  500 . The computer  500  may store and process the data store  400  of  FIG. 4 . The computer  500  includes a processor  505 , a memory  510 , communication hardware  515 , and a storage device  520 . 
     The memory  510  may store computer readable program code. The processor  505  may execute the computer readable program code. The computer  500  may communicate through the communication hardware  515 . The storage device  520  may also store the computer readable program code. 
       FIG. 6  is a schematic block diagram illustrating one embodiment of an interior location identification apparatus  600 . The apparatus  600  may perform functions of interior location identification. The description of the apparatus  600  refers to elements of  FIGS. 1-5 , like numbers referring to like elements. The apparatus  600  includes a parse module  605 , a search module  610 , the first image  615 , the second image  620 , stored objects  625 , parsed objects  630 , and second objects  635 . The parse module  605 , search module  610 , first image  615 , second image  620 , stored objects  625 , parsed objects  630 , and second objects  635  may be embodied in computer readable program code stored in the memory  510  and/or the storage device  520  and executed by the processor  505 . In one embodiment, the parse module  605  and the search module  610  are embodied in separate computers  500 . Alternatively, the parse module  605  and the search module  610  may be embodied in a single computer  500 . 
     The parse module  605  parses at least one object  630  from the first image  615  of the interior space  100 . In addition, the parse module compares each parsed object  630  with a plurality of stored objects  625 . The stored objects  625  may the first objects  305  stored in the data store  400 . Alternatively, the stored objects  625  may be stored in a separate data structure. 
     The parse module  605  selects a parsed object  630  that is differentiated from the stored objects  625  as the first object  305 . In addition, the parse module  605  indexes a location description  350  of the interior space  100  with the first object  305  in a location record  300 . 
     The search module  610  identifies the first object  305  from a second image  620  of the interior space  100 . The second image  620  may be the image  200 . The search module  610  retrieves the location description  350  from the data store  400  in response to identifying the first object  305 . 
       FIG. 7  is a schematic flow chart diagram illustrating one embodiment of an interior location storage method  700 . The method  700  may perform functions of the interior location identification apparatus  600  of  FIG. 6 . The description of the method  700  refers to elements of  FIGS. 1-6 , like numbers referring to like elements. 
     The method  700  starts, and in one embodiment the camera  140  scans  705  the first image  615 . The camera  140  may scan  705  the first image  615  as part of a systematic cataloging of images and location descriptions for the building. Alternatively, the camera  140  may scan  705  the first image  615  as part of a voluntary submission of information regarding the interior space  100 . For example, an occupant of the interior space  100  may submit the first image  615  to identify the location of the interior space  100 . 
     The parse module  605  may parse  710  one or more objects  630  from the first image  615  of the interior space  100 . In one embodiment, the parse module  605  employs a pattern recognition algorithm to parse  710  the objects  630 . The parse module  605  may identify boundaries for a parsed object  630 , remove background pixels from the parsed object  630 , and record the parsed object  630  as a distinct data file. 
     The parse module  605  may determine characteristics of the parsed object  630 . For example, the parse module  605  may perform a hash algorithm to generate a hash of the parsed object  630 . Alternatively, the parse module  605  may perform a Fourier transform on the parsed object  630  to generate a transform of the parsed object  630 . In addition, the parse module  605  may determine other characteristics of the parsed object  630  including but not limited to one or more colors, one or more average colors, one or more shapes, one or more tones, one or more hues, vectors for one or more lines, and one or more reflectivity values for the parsed object  630 . 
     In one embodiment, the parse module  605  compares  715  the parsed objects  630  from the first image  615  with one or more stored objects  625 . The stored objects  625  may be first objects  305  stored in location records  300  of the data store  400 . Alternatively, the stored objects  625  may be embodied in a database of common objects. For example, a computer monitor object may be included in the stored objects  630  and classified as a common object that is less likely to provide location clues. Other stored objects may be identified as likely to provide location clues. 
     The parse module  605  may compare  715  characteristics of the parsed object  630  with characteristics of the stored objects  625 . The parse module  605  may calculate a plurality of characteristic scores from the characteristics of each parsed object  630 . The parse module  605  may further compare  715  the parsed object characteristic scores with characteristic scores of the stored objects  625 . 
     The parse module  605  may calculate a similarity score for each characteristic as a difference between the characteristic of a parsed object  630  and the same characteristic of a stored object  625 . In addition, the parse module  605  may calculate a characteristic difference score as a sum of products of similarity scores and weights. Equation 1 illustrates one embodiment of calculating the characteristic difference score C where each k i  is a weight that is greater than zero and s i  is a similarity score.
 
 C=Σk   i   *s   i   Equation 1
 
     In an alternate embodiment, the parse module  605  compares  715  the parsed objects  630  with the stored objects  625  based on the spatial relationships between the parsed objects  630  and the stored objects  625 . For example, the spatial relationship of three computer monitors in a first object  305  may uniquely identify a location of the interior space  100  although the computer monitors are not individually unique. To determine if a spatial relationship may identify the interior space  100 , the parse module  605  may co-locate a first parsed object  630  and a first stored object  625  within a spatial system. The parse module  605  may further calculate a spatial difference score as a sum of differences between each other parsed object  630  and corresponding stored objects  625  that are spatially related to the first stored object  625 . 
     In one embodiment, the parse module  605  excludes from consideration parsed objects that are identified as mobile. For example, the parse module  605  may identify a parsed object  630  as a purse by comparing the parsed object with a plurality of purse stored objects  625 . The parse module  605  may exclude the purse parsed object  630 . 
     In one embodiment, the parse module  605  selects  720  one or more parsed objects  630  as the first object  305 . The parse module  605  may select  720  parsed objects  630  that are most differentiated from the stored objects  625 . For example, the parse module  605  may select  720  parsed object with a lowest characteristic difference score, a lowest spatial difference score, and/or combinations thereof. 
     The parse module  605  further indexes  725  the location description  350  for the interior space  100  with the selected first object  305  to form the location record  300 . In one embodiment, the location description  350  may be recorded in the location record  300  by an automated device, from an entry, or combinations thereof. Thus the location description  350  may be retrieved for identifying the location of the interior space  100  as will be described hereafter. 
     In one embodiment, the parse module  605  appends  730  the last GPS coordinate  335  to the location record  300 . The last GPS coordinate  335  may be a most recent GPS coordinate recorded by a device such as the camera  140 . The last GPS coordinate  335  may not accurately indicate the location of the interior space  100 . However, the last GPS coordinate  335  may be near to the interior space  100 . 
     The parse module  605  may further append  735  the absolute position  740  to the location record  300 . The absolute position  740  may be entered at a later date. In addition, the parse module  605  may store  740  the location record  300  in the data store  400  and the method  700  ends. 
     The method  700  scans  705 , parses  710 , and selects  720  first objects  305  that may subsequently be used to recover the location record  300  and the location information  350  for identifying the interior space  100 . 
       FIG. 8  is a schematic flow chart diagram illustrating one embodiment of an interior location identification method  800 . The method  800  may perform functions of the interior location identification apparatus  600  of  FIG. 6 . The description of the method  800  refers to elements of  FIGS. 1-7 , like numbers referring to like elements. 
     The method  800  starts, and in one embodiment, the camera  140  scans  805  the second image  620  from the interior space  100 . In a certain embodiment, the second image  620  comprises a plurality of images  200 . The plurality of images  200  may be digitally combined into a single image. Images may be a Motion Picture Experts Group (MPEG)-1 file, an MPEG-2 file, an MPEG-3 file, an MPEG-4 file, an MPEG-7 file, an MPEG-21 file, Portable Network Graphics (PNG) file, a Joint Photographic Experts Group (JPEG) file, a Graphics Interchange Format (GIF) file, or the like. 
     The camera  140  may be embodied in device such as a cellular telephone, a tablet computer, a notebook computer, portable electronic device, or the like. The camera  140  may scan  805  the second image  620  to identify the location of the interior space  100 . 
     In one embodiment, the search module  610  narrows  810  a scope of the search. The search module  610  may narrow  810  the scope of the search to location records  300  with last GPS coordinates  335  and/or absolute positions  340  within a specified radius of a last GPS coordinate measured by the device. The specified radius may be in the range of 25 to 200 meters. For example, the device may record a current last GPS coordinate. The search module  610  may only consider location records  300  wherein the last GPS coordinate  335  and/or the absolute position  340  is within 100 meters of the current last GPS coordinates. 
     In one embodiment, the search module determines an estimated location by triangulating one or more signals including but not limited to cellular telephone signals, broadcast signals, and/or wireless network signals. The search module  610  may narrow the search by only considering location records  300  wherein the last GPS coordinate  335  and/or the absolute positioned  340  is within 100 meters of the estimated location. 
     Alternatively, the search module  610  may narrow  810  the scope of the search to location records  300  with secondary location indications  330  that match a secondary location indication  330  that is identified that the current location. For example, if the search module  610  detects a WiFi network named “plazaonenet,” the search module  610  may narrow  810  the scope of the search to location records  300  with a least one secondary location indication  330  comprising a WiFi network named “plazaonenet.” 
     The search module  610  identifies  815  the first object  305  of a location record  300  from the second image  615 . In one embodiment, the search module  610  employs a pattern recognition algorithm to parse second objects  635  from the second image. The parse module  605  may identify boundaries for a second object  635 , remove background pixels from the second object  635 , and record the second object  635  as a distinct data file. 
     The search module  610  may determine characteristics of the second object  635 . For example, the search module  610  may perform a hash algorithm to generate a hash of the second object  635 . Alternatively, the search module  610  may perform a Fourier transform on the second object  635  to generate a transform of the second object  635 . In addition, the search module  610  may determine other characteristics of the second object  635  including but not limited to one or more colors, one or more average colors, one or more hues, one or more shapes, vectors for one or more lines, one or more tones values, and one or more reflectivity values. 
     The search module  610  may calculate a plurality of characteristic scores from the characteristics of each parsed second object  635 . The search module  610  may further compare the parsed second object characteristic scores with characteristic scores of the first objects  305 . In one embodiment, the search module  610  calculates with a characteristic difference score, a lowest spatial difference score, and/or combinations thereof for each parsed second object  635  and each first object  305  and identifies  815  the first object  305  from the data store  400  with the smallest differences in characteristic difference scores and/or spatial difference scores. In an alternate embodiment, the search module  610  identifies  815  a plurality of first objects  305  that each exceeds a match threshold. 
     In one embodiment, the search module  610  retrieves  820  a location description  350  from the location record  300  of the identified first object  305  and the method  800  ends. The search module  610  may also retrieve  820  a plurality location descriptions  350  for first objects  305  that exceed the match threshold. The search module  610  may present the location description  350  on a display, provide an audible rendering, communicate the location description to another device, or the like. Thus a device employing an embodiment is enabled to identify the location of the interior space  100  even if no GPS signal is available. 
     The embodiments may be practiced in other specific forms. The described embodiments are to be considered in all respects only as illustrative and not restrictive. The scope of the invention is, therefore, indicated by the appended claims rather than by the foregoing description. All changes which come within the meaning and range of equivalency of the claims are to be embraced within their scope.