Patent ID: 12238404

DETAILED DESCRIPTION

The description that follows includes systems, methods, techniques, instruction sequences, and computing machine program products that embody illustrative embodiments of the disclosure. In the following description, for the purposes of explanation, numerous specific details are set forth in order to provide an understanding of various embodiments of the inventive subject matter. It will be evident, however, to those skilled in the art, that embodiments of the inventive subject matter may be practiced without these specific details. In general, well-known instruction instances, protocols, structures, and techniques are not necessarily shown in detail.

Dolly zoom is a complex camera effect achieved by using a zoom to adjust the angle of view of a captured image while the point of view moves toward or away from the subject to keep the subject the same size in the frame. For a camera system, this generally requires a dolly or guidance system and a zoom lens that work in concert to produce a zooming effect. An example of the dolly zoom effect can be found in movies such as Jaws and Goodfellas. Performing a dolly zoom effect on a resource-constrained device, such as a smartphone, is generally not possible because the device has limited resources, such as processing power and memory, usually required for complex video processing. Further, the devices lack resources such as a dolly or guidance system and a zoom system (e.g., zoom lens) that can work in concert (e.g., work in concert to produce a dolly zoom effect).

A scaled perspective zoom effect can be implemented on resource-constrained devices to perform a dolly zoom-like effect. According to some example embodiments, a client device (e.g., smartphone) may display a live video feed of video being captured by a camera of the client device. The live video feed may display a subject (e.g., a person) in front of a background (e.g., a grassy field with trees). The user of the client device may select the person as a target feature by tapping on the depiction of the person in the live video feed. The client device is configured to receive the tapping motion and detect the person as the target feature, according to some example embodiments. The client device may provide a mesh over the person's face to track the person's face in the live video feed. The client device is then physically moved towards the person. The physical movement of the client device towards the person causes the perspective of both the foreground person and the background (e.g., the grassy field with trees) to change. As the client device records the person and background while moving towards the person, the client device keeps the size of the person as displayed in the live video feed the same. The resulting effect of changing the perspective of the background while maintaining the size of the person produces a type of dolly zoom effect that works well on resource-constrained devices. The above description is a high-level example embodiment; further example embodiments are discussed in detail below with reference to the figures.

FIG.1is a block diagram showing an example messaging system100for exchanging data (e.g., messages and associated content) over a network. The messaging system100includes multiple client devices102, each of which hosts a number of applications including a messaging client application104. Each messaging client application104is communicatively coupled to other instances of the messaging client application104and a messaging server system108via a network106(e.g., the Internet).

Accordingly, each messaging client application104is able to communicate and exchange data with another messaging client application104and with the messaging server system108via the network106. The data exchanged between messaging client applications104, and between a messaging client application104and the messaging server system108, includes functions (e.g., commands to invoke functions) as well as payload data (e.g., text, audio, video, or other multimedia data).

The messaging server system108provides server-side functionality via the network106to a particular messaging client application104. While certain functions of the messaging system100are described herein as being performed by either a messaging client application104or by the messaging server system108, it will be appreciated that the location of certain functionality within either the messaging client application104or the messaging server system108is a design choice. For example, it may be technically preferable to initially deploy certain technology and functionality within the messaging server system108, but to later migrate this technology and functionality to the messaging client application104where a client device102has a sufficient processing capacity.

The messaging server system108supports various services and operations that are provided to the messaging client application104. Such operations include transmitting data to, receiving data from, and processing data generated by the messaging client application104. This data may include message content, client device information, geolocation information, media annotation and overlays, message content persistence conditions, social network information, and live event information, as examples. Data exchanges within the messaging system100are invoked and controlled through functions available via user interfaces (UIs) of the messaging client application104.

Turning now specifically to the messaging server system108, an Application Programming Interface (API) server110is coupled to, and provides a programmatic interface to, an application server112. The application server112is communicatively coupled to a database server118, which facilitates access to a database120in which is stored data associated with messages processed by the application server112.

The API server110receives and transmits message data (e.g., commands and message payloads) between the client device102and the application server112. Specifically, the API server110provides a set of interfaces (e.g., routines and protocols) that can be called or queried by the messaging client application104in order to invoke functionality of the application server112. The API server110exposes various functions supported by the application server112, including account registration; login functionality; the sending of messages, via the application server112, from a particular messaging client application104to another messaging client application104; the sending of media files (e.g., images or video) from a messaging client application104to a messaging server application114for possible access by another messaging client application104; the setting of a collection of media data (e.g., a story); the retrieval of such collections; the retrieval of a list of friends of a user of a client device102; the retrieval of messages and content; the adding and deletion of friends to and from a social graph; the location of friends within the social graph; and opening and application events (e.g., relating to the messaging client application104).

The application server112hosts a number of applications and subsystems, including the messaging server application114, an image processing system116, and a social network system122. The messaging server application114implements a number of message processing technologies and functions, particularly related to the aggregation and other processing of content (e.g., textual and multimedia content) included in messages received from multiple instances of the messaging client application104. As will be described in further detail, the text and media content from multiple sources may be aggregated into collections of content (e.g., called stories or galleries). These collections are then made available, by the messaging server application114, to the messaging client application104. Other processor- and memory-intensive processing of data may also be performed server-side by the messaging server application114, in view of the hardware requirements for such processing.

The application server112also includes the image processing system116, which is dedicated to performing various image processing operations, typically with respect to images or video received within the payload of a message at the messaging server application114.

The social network system122supports various social networking functions and services, and makes these functions and services available to the messaging server application114. To this end, the social network system122maintains and accesses an entity graph (e.g., entity graph304inFIG.3) within the database120. Examples of functions and services supported by the social network system122include the identification of other users of the messaging system100with whom a particular user has relationships or whom the particular user is “following”, and also the identification of other entities and interests of a particular user.

The application server112is communicatively coupled to a database server118, which facilitates access to a database120in which is stored data associated with messages processed by the messaging server application114.

FIG.2is block diagram illustrating further details regarding the messaging system100, according to example embodiments. Specifically, the messaging system100is shown to comprise the messaging client application104and the application server112, which in turn embody a number of subsystems, namely an ephemeral timer system202, a collection management system204, an annotation system206, and a scaled perspective zoom system150. The scaled perspective zoom system150is discussed in further detail below.

The ephemeral timer system202is responsible for enforcing the temporary access to content permitted by the messaging client application104and the messaging server application114. To this end, the ephemeral timer system202incorporates a number of timers that, based on duration and display parameters associated with a message or collection of messages (e.g., a SNAPCHAT Story), selectively display and enable access to messages and associated content via the messaging client application104. Further details regarding the operation of the ephemeral timer system202are provided below.

The collection management system204is responsible for managing collections of media (e.g., collections of text, image, video, and audio data). In some examples, a collection of content (e.g., messages, including images, video, text, and audio) may be organized into an “event gallery” or an “event story”. Such a collection may be made available for a specified time period, such as the duration of an event to which the content relates. For example, content relating to a music concert may be made available as a “story” for the duration of that music concert. The collection management system204may also be responsible for publishing an icon that provides notification of the existence of a particular collection to the user interface of the messaging client application104.

The collection management system204furthermore includes a curation interface208that allows a collection manager to manage and curate a particular collection of content. For example, the curation interface208enables an event organizer to curate a collection of content relating to a specific event (e.g., delete inappropriate content or redundant messages). Additionally, the collection management system204employs machine vision (or image recognition technology) and content rules to automatically curate a content collection. In certain embodiments, compensation may be paid to a user for inclusion of user-generated content into a collection. In such cases, the curation interface208operates to automatically make payments to such users for the use of their content.

The annotation system206provides various functions that enable a user to annotate or otherwise modify or edit media content associated with a message. For example, the annotation system206provides functions related to the generation and publishing of media overlays for messages processed by the messaging system100. The annotation system206operatively supplies a media overlay (e.g., a SNAPCHAT Geofilter or filter) to the messaging client application104based on a geolocation of the client device102. In another example, the annotation system206operatively supplies a media overlay to the messaging client application104based on other information, such as social network information of the user of the client device102. A media overlay may include audio and visual content and visual effects. Examples of audio and visual content include pictures, texts, logos, animations, and sound effects. An example of a visual effect includes color overlaying. The audio and visual content or the visual effects can be applied to a media content item (e.g., a photo) at the client device102. For example, the media overlay includes text that can be overlaid on top of a photograph generated by the client device102. In another example, the media overlay includes an identification of a location (e.g., Venice Beach), a name of a live event, or a name of a merchant (e.g., Beach Coffee House). In another example, the annotation system206uses the geolocation of the client device102to identify a media overlay that includes the name of a merchant at the geolocation of the client device102. The media overlay may include other indicia associated with the merchant. The media overlays may be stored in the database120and accessed through the database server118.

In one example embodiment, the annotation system206provides a user-based publication platform that enables users to select a geolocation on a map, and upload content associated with the selected geolocation. The user may also specify circumstances under which particular content should be offered to other users. The annotation system206generates a media overlay that includes the uploaded content and associates the uploaded content with the selected geolocation.

In another example embodiment, the annotation system206provides a merchant-based publication platform that enables merchants to select a particular media overlay associated with a geolocation via a bidding process. For example, the annotation system206associates the media overlay of a highest-bidding merchant with a corresponding geolocation for a predefined amount of time

FIG.3is a schematic diagram illustrating data300which may be stored in the database120of the messaging server system108, according to certain example embodiments. While the content of the database120is shown to comprise a number of tables, it will be appreciated that the data could be stored in other types of data structures (e.g., as an object-oriented database).

The database120includes message data stored within a message table314. An entity table302stores entity data, including an entity graph304. Entities for which records are maintained within the entity table302may include individuals, corporate entities, organizations, objects, places, events, etc. Regardless of type, any entity regarding which the messaging server system108stores data may be a recognized entity. Each entity is provided with a unique identifier, as well as an entity type identifier (not shown).

The entity graph304furthermore stores information regarding relationships and associations between or among entities. Such relationships may be social, professional (e.g., work at a common corporation or organization), interested-based, or activity-based, merely for example.

The database120also stores annotation data, in the example form of filters, in an annotation table312. Filters for which data is stored within the annotation table312are associated with and applied to videos (for which data is stored in a video table310) and/or images (for which data is stored in an image table308). Filters, in one example, are overlays that are displayed as overlaid on an image or video during presentation to a recipient user. Filters may be of various types, including user-selected filters from a gallery of filters presented to a sending user by the messaging client application104when the sending user is composing a message. Other types of filters include geolocation filters (also known as geo-filters) which may be presented to a sending user based on geographic location. For example, geolocation filters specific to a neighborhood or special location may be presented within a user interface by the messaging client application104, based on geolocation information determined by a Global Positioning System (GPS) unit of the client device102. Another type of filter is a data filter, which may be selectively presented to a sending user by the messaging client application104, based on other inputs or information gathered by the client device102during the message creation process. Examples of data filters include a current temperature at a specific location, a current speed at which a sending user is traveling, a battery life for a client device102, or the current time.

Other annotation data that may be stored within the image table308is so-called “lens” data. A “lens” may be a real-time special effect and sound that may be added to an image or a video.

As mentioned above, the video table310stores video data which, in one embodiment, is associated with messages for which records are maintained within the message table314. Similarly, the image table308stores image data associated with messages for which message data is stored in the message table314. The entity table302may associate various annotations from the annotation table312with various images and videos stored in the image table308and the video table310.

A story table306stores data regarding collections of messages and associated image, video, or audio data, which are compiled into a collection (e.g., a SNAPCHAT Story or a gallery). The creation of a particular collection may be initiated by a particular user (e.g., each user for whom a record is maintained in the entity table302). A user may create a “personal story” in the form of a collection of content that has been created and sent/broadcast by that user. To this end, the user interface of the messaging client application104may include an icon that is user-selectable to enable a sending user to add specific content to his or her personal story.

A collection may also constitute a “live story”, which is a collection of content from multiple users that is created manually, automatically, or using a combination of manual and automatic techniques. For example, a “live story” may constitute a curated stream of user-submitted content from various locations and events. Users whose client devices have location services enabled and are at a common location or event at a particular time may, for example, be presented with an option, via a user interface of the messaging client application104, to contribute content to a particular live story. The live story may be identified to the user by the messaging client application104, based on his or her location. The end result is a “live story” told from a community perspective.

A further type of content collection is known as a “location story”, which enables a user whose client device102is located within a specific geographic location (e.g., on a college or university campus) to contribute to a particular collection. In some embodiments, a contribution to a location story may require a second degree of authentication to verify that the end user belongs to a specific organization or other entity (e.g., is a student on the university campus).

FIG.4is a schematic diagram illustrating a structure of a message400, according to some embodiments, generated by a messaging client application104for communication to a further messaging client application104or the messaging server application114. The content of a particular message400is used to populate the message table314stored within the database120, accessible by the messaging server application114. Similarly, the content of a message400is stored in memory as “in-transit” or “in-flight” data of the client device102or the application server112. The message400is shown to include the following components:A message identifier402: a unique identifier that identifies the message400.A message text payload404: text, to be generated by a user via a user interface of the client device102, and that is included in the message400.A message image payload406: image data, captured by a camera component of a client device102or retrieved from memory of a client device102, and that is included in the message400.A message video payload408: video data, captured by a camera component or retrieved from a memory component of the client device102, and that is included in the message400.A message audio payload410: audio data, captured by a microphone or retrieved from the memory component of the client device102, and that is included in the message400.Message annotations412: annotation data (e.g., filters, stickers, or other enhancements) that represents annotations to be applied to the message image payload406, message video payload408, or message audio payload410of the message400.A message duration parameter414: a parameter value indicating, in seconds, the amount of time for which content of the message400(e.g., the message image payload406, message video payload408, and message audio payload410) is to be presented or made accessible to a user via the messaging client application104.A message geolocation parameter416: geolocation data (e.g., latitudinal and longitudinal coordinates) associated with the content payload of the message400. Multiple message geolocation parameter416values may be included in the payload, each of these parameter values being associated with respective content items included in the content (e.g., a specific image in the message image payload406, or a specific video in the message video payload408).A message story identifier418: identifier values identifying one or more content collections (e.g., “stories”) with which a particular content item in the message image payload406of the message400is associated. For example, multiple images within the message image payload406may each be associated with multiple content collections using identifier values.A message tag420: one or more tags, each of which is indicative of the subject matter of content included in the message payload. For example, where a particular image included in the message image payload406depicts an animal (e.g., a lion), a tag value may be included within the message tag420that is indicative of the relevant animal. Tag values may be generated manually, based on user input, or may be automatically generated using, for example, image recognition.A message sender identifier422: an identifier (e.g., a messaging system identifier, email address, or device identifier) indicative of a user of the client device102on which the message400was generated and from which the message400was sent.A message receiver identifier424: an identifier (e.g., a messaging system identifier, email address, or device identifier) indicative of a user of the client device102to which the message400is addressed.

The contents (e.g., values) of the various components of the message400may be pointers to locations in tables within which content data values are stored. For example, an image value in the message image payload406may be a pointer to (or address of) a location within the image table308. Similarly, values within the message video payload408may point to data stored within the video table310, values stored within the message annotations412may point to data stored in the annotation table312, values stored within the message story identifier418may point to data stored in the story table306, and values stored within the message sender identifier422and the message receiver identifier424may point to user records stored within the entity table302.

FIG.5is a schematic diagram illustrating an access-limiting process500, in terms of which access to content (e.g., an ephemeral message502, and associated multimedia payload of data) or a content collection (e.g., an ephemeral message story504) may be time-limited (e.g., made ephemeral).

An ephemeral message502is shown to be associated with a message duration parameter506, the value of which determines an amount of time that the ephemeral message502will be displayed to a receiving user of the ephemeral message502by the messaging client application104. In one embodiment, where the messaging client application104is a SNAPCHAT application client, an ephemeral message502is viewable by a receiving user for up to a maximum of 10 seconds, depending on the amount of time that the sending user specifies using the message duration parameter506.

The message duration parameter506and the message receiver identifier424are shown to be inputs to a message timer512, which is responsible for determining the amount of time that the ephemeral message502is shown to a particular receiving user identified by the message receiver identifier424. In particular, the ephemeral message502will only be shown to the relevant receiving user for a time period determined by the value of the message duration parameter506. The message timer512is shown to provide output to a more generalized ephemeral timer system202, which is responsible for the overall timing of display of content (e.g., an ephemeral message502) to a receiving user.

The ephemeral message502is shown inFIG.5to be included within an ephemeral message story504(e.g., a personal SNAPCHAT Story, or an event story). The ephemeral message story504has an associated story duration parameter508, a value of which determines a time duration for which the ephemeral message story504is presented and accessible to users of the messaging system100. The story duration parameter508, for example, may be the duration of a music concert, where the ephemeral message story504is a collection of content pertaining to that concert. Alternatively, a user (either the owning user or a curator user) may specify the value for the story duration parameter508when performing the setup and creation of the ephemeral message story504.

Additionally, each ephemeral message502within the ephemeral message story504has an associated story participation parameter510, a value of which determines the duration of time for which the ephemeral message502will be accessible within the context of the ephemeral message story504. Accordingly, a particular ephemeral message502may “expire” and become inaccessible within the context of the ephemeral message story504, prior to the ephemeral message story504itself expiring in terms of the story duration parameter508. The story duration parameter508, story participation parameter510, and message receiver identifier424each provide input to a story timer514, which operationally determines whether a particular ephemeral message502of the ephemeral message story504will be displayed to a particular receiving user and, if so, for how long. Note that the ephemeral message story504is also aware of the identity of the particular receiving user as a result of the message receiver identifier424.

Accordingly, the story timer514operationally controls the overall lifespan of an associated ephemeral message story504, as well as an individual ephemeral message502included in the ephemeral message story504. In one embodiment, each and every ephemeral message502within the ephemeral message story504remains viewable and accessible for a time period specified by the story duration parameter508. In a further embodiment, a certain ephemeral message502may expire, within the context of the ephemeral message story504, based on a story participation parameter510. Note that a message duration parameter506may still determine the duration of time for which a particular ephemeral message502is displayed to a receiving user, even within the context of the ephemeral message story504. Accordingly, the message duration parameter506determines the duration of time that a particular ephemeral message502is displayed to a receiving user, regardless of whether the receiving user is viewing that ephemeral message502inside or outside the context of an ephemeral message story504.

The ephemeral timer system202may furthermore operationally remove a particular ephemeral message502from the ephemeral message story504based on a determination that it has exceeded an associated story participation parameter510. For example, when a sending user has established a story participation parameter510of 24 hours from posting, the ephemeral timer system202will remove the relevant ephemeral message502from the ephemeral message story504after the specified 24 hours. The ephemeral timer system202also operates to remove an ephemeral message story504either when the story participation parameter510for each and every ephemeral message502within the ephemeral message story504has expired, or when the ephemeral message story504itself has expired in terms of the story duration parameter508.

In certain use cases, a creator of a particular ephemeral message story504may specify an indefinite story duration parameter508. In this case, the expiration of the story participation parameter510for the last remaining ephemeral message502within the ephemeral message story504will determine when the ephemeral message story504itself expires. In this case, a new ephemeral message502, added to the ephemeral message story504, with a new story participation parameter510, effectively extends the life of an ephemeral message story504to equal the value of the story participation parameter510.

In response to the ephemeral timer system202determining that an ephemeral message story504has expired (e.g., is no longer accessible), the ephemeral timer system202communicates with the messaging system100(e.g., specifically, the messaging client application104) to cause an indicium (e.g., an icon) associated with the relevant ephemeral message story504to no longer be displayed within a user interface of the messaging client application104. Similarly, when the ephemeral timer system202determines that the message duration parameter506for a particular ephemeral message502has expired, the ephemeral timer system202causes the messaging client application104to no longer display an indicium (e.g., an icon or textual identification) associated with the ephemeral message502.

FIG.6shows a functional architecture for a scaled perspective zoom system150, according to some example embodiments. As illustrated, the scaled perspective zoom system150comprises a capture engine605, a feature engine610, an interface engine615, a scale engine620, a stabilization engine625, a distribution engine630, and an enhancement engine635. The capture engine605manages interfacing with an image sensor (e.g., CMOS, CCD) integrated into a client device to capture one or more images (e.g., a live feed). The feature engine610is configured to detect a subject depicted within one or more images as a target feature. The interface engine615is configured to receive inputs from a user of the client device. For example, the interface engine615may receive a user input (e.g., a gesture such as a two-finger tap, a button click) from the user that indicates that the user seeks to assign a given object as a target object, as discussed in further detail below. The scale engine620is responsible for managing the scale (e.g., apparent size) of the target feature. For example, as the client device moves closer to or farther away from the subject, the apparent size of the subject may change. To compensate for the change, the scale engine620may maintain the scale of the target feature so that it appears that the target feature is maintaining the same size. The stabilization engine625is configured to stabilize the target feature within the one or more images as the client device physically moves. The distribution engine630is configured to save the one or more images capturing the scaled perspective zoom effect to local memory. Further, the distribution engine630is configured to transmit the one or more images capturing the scaled perspective zoom effect to a social networking service (e.g., publish the one or more images as an ephemeral message502). The enhancement engine635is configured to modify the background of the one or more images. For example, the background may be replaced with a computer-generated background, which is saved with the one or more images.

FIG.7shows a flow diagram of a method700for generating a scaled perspective zoom effect on one or more images, according to some example embodiments. At operation705, the capture engine605captures one or more images using an image sensor of the client device102. For example, the one or more images may be a live video feed displayed on a screen of the client device102in real time as the images are captured. At operation710, the interface engine615receives an input to modify a subject depicted in the one or more images. For example, the user may tap and hold his/her finger on a person's face depicted in the live video feed on the display screen of the client device102. At operation715, in response to the input, the feature engine610identifies a target feature in the one or more images. For example, the feature engine610may initiate face detection on the one or more images in the area indicated by the input (e.g., over the person's face). At operation720, the scale engine620scales the target feature as the background moves. For example, once the face is detected, and while the user keeps his/her finger pressed on the person's depicted face, the user can move the client device102farther away from the person. As the client device102moves farther away, the apparent size of the person's face will decrease in the live video feed. However, as the person's face has been detected by the feature engine610, the scale engine620can maintain the apparent size of the person's face, even as the client device102moves away. The resulting effect is a scaled perspective zoom as the target feature maintains its size while the perspective of the background changes. In this way, a client device can implement a scaled perspective zoom effect without a guidance system (e.g., dolly) or a controlled zoom.

Further, according to some example embodiments, the client device is equipped with a zoom system (e.g., physical zoom lens) that the user can implement in operation720. For example, once the target feature is detected, the size of the target feature can be maintained as the user moves the camera while adjusting the zooming system. The resulting effect can produce different types of dolly zoom effects, according to some example embodiments.

At operation725, the distribution engine630stores the one or more images that capture the perspective zoom effect. For example, the distribution engine630stores the one or more images as a zoom sequence to a local memory of the client device102. At operation730, the distribution engine630transmits the one or more images that capture the perspective zoom effect over a network. For example, the distribution engine630may publish the zoom sequence to the social network system122from the social network system user profile of the user. In some example embodiments, the zoom sequence is published as an ephemeral message502within an ephemeral message story504, as discussed above with reference toFIG.5.

FIG.8shows a flow diagram of a method800for identifying one or more target features, according to some example embodiments. One or more of the operations of the method800can be performed as sub-routines of operation715inFIG.7. At operation805, the feature engine610identifies one or more features by performing face detection within the one or more images. For example, the feature engine610may implement the Viola-Jones algorithm to detect the face, and use points on the face to create a mesh that tracks the face in each of the one or more images. At operation810, the feature engine610identifies one or more features by performing body detection within the one or more images. For example, the feature engine610may use a convolutional neural network to detect a person's body, and further break up the person's body into labeled segments, as discussed in further detail below. Further details regarding body detection are described in Provisional Application Ser. No. 62/481,415, titled “GENERATING A PIXEL MASK USING MACHINE LEARNING”, filed on Apr. 4, 2017, which is hereby incorporated by reference in its entirety.

At operation815, the feature engine610identifies one or more features by performing shape detection within the one or more images. For example, the feature engine610may implement edge detection to determine the outline of an object. At operation820, the feature engine610sets the features detected within at least one of the operations805-815as the target feature. It is to be appreciated that although the example method800displays all of the operations805-815being implemented, in some example embodiments one or more of the operations805-815are implemented depending on how the feature engine610is configured. For example, in some example embodiments, the feature engine610is configured with only face-detection capabilities. In those example embodiments, in response to a user tapping on a face in the one or more images, the feature engine610performs face detection as discussed above, and body and shape detection may never occur. Further, in some example embodiments, one of the feature detection operations (operations805-815) may complement or enhance the result of another feature detection operation. For example, at operation805face detection may detect a person's face and track it using a mesh, and operation810may be skipped. Then, at operation815, the feature engine610may perform shape detection to detect the neck and shoulders of the person. Finally, at operation820, the face, neck, and shoulders may all be set as the target feature.

FIG.9shows a flow diagram of a method900for scaling a target feature in the one or more images, according to some example embodiments. One or more of the operations of the method900can be performed as sub-routines of operation720inFIG.7. At operation905, the interface engine615receives an input to resize the target feature (e.g., increase or decrease the size). For example, the user performs a pinch-and-zoom-in gesture on the target feature to indicate that he/she seeks to enlarge the target feature. At operation910, the scale engine620resizes the target feature according to the input. For example, the scale engine620uses a mesh of a face to enlarge the size of the face on the display screen of the client device.

At operation915, the scale engine620maintains the size (e.g., the enlarged size) of the target feature as the background moves. For example, at operation915, the client device is moved closer to the depicted subject while the live feed is centered on the depicted subject, thereby causing the background to move in the one or more images. Thus, in the live feed, the background changes its perspective due to physical movement of the client device. Further, due to the target feature being enlarged, as the depicted subject's apparent size grows due to the client device moving closer, the enlarged target feature covers the growing depicted subject.

Although the example method900implements resizing of the target feature, in some example embodiments, the target feature is not initially resized before the background moves. That is, in an initial frame of the live feed, the target feature is detected and its initial size upon being detected is maintained at operation915as the background moves. This approach may be implemented, for example, when the increasing or decreasing apparent size of the depicted image due to the client device moving is negligible.

The size of the target feature can be pixel size of the target feature in the one or more images, according to some example embodiments. Further, the initial size of the target feature may be a percentage of the total image size (e.g., an image frame of the live feed), according to some example embodiments. For example, the initial size of the target feature may be 30% of the height of the image frame of the live feed. As the background is moved, the target feature's dimensions are manipulated to remain at 30% of the image frame even though the apparent size of the depicted object may be changing due to the client device moving closer or farther away.

At operation920, the stabilization engine625stabilizes the target feature in its initial area (e.g., the center of the one or more images) as the background moves (e.g., due to the client device moving closer to the depicted subject). Stabilization of the target feature helps maintain the smoothness of the scaled perspective zoom effect in the absence of a dolly guidance system. In some example embodiments, the stabilization engine625performs stabilization by keeping the target feature in the center of the one or more images with respect to edges of the images. In some example embodiments, the stabilization engine625performs stabilization by keeping the position of the target feature constant with respect to an object detected in the one or more images. For example, if in an initial image the face is 50 pixels to the left of a tree, the stabilization engine625repositions the target feature such that it stays 50 pixels to the left of the tree in each image of the live feed.

Although the above discussion of the method900uses an enlarged target feature example (e.g., enlarging in response to a pinch-and-zoom-in gesture), it is to be appreciated that a corresponding approach can be implemented using a decreased-size target feature. In those embodiments, for example, at operation905the user decreases the size by using a pinch-and-zoom-out gesture.

FIG.10shows a flow diagram of a method1000for positively scaling a target feature in the one or more images, according to some example embodiments. One or more of the operations of the method1000can be performed as sub-routines of operation720inFIG.7. The method1000is similar to the method900except that instead of being maintained as the background moves (e.g., due to the client device physically moving), the target feature's size is increased progressively in each subsequent frame of the live feed as the background moves. This approach, e.g., the method1000, can increase the effect of the scaled perspective zoom. Accordingly, at operation1005, the interface engine615receives an input to resize the target feature (e.g., receives an input to increase or decrease the initial size of the target feature). At operation1010, the scale engine620resizes the target feature according to the input. At operation1015, the scale engine620positively scales the target feature so that the size of the target feature increases as the background moves (e.g., due to the client device moving). At operation1020, the stabilization engine625stabilizes the target feature in its location (e.g., the center of the one or more images) as the background moves.

FIG.11shows a flow diagram of a method1100for negatively scaling a target feature in the one or more images, according to some example embodiments. One or more of the operations of the method1100can be performed as sub-routines of operation720inFIG.7. The method1100is similar to the method900except that instead of being maintained as the background moves (e.g., due to the client device physically moving), the target feature's size is decreased progressively in each subsequent frame of the live feed as the background moves. This approach, e.g., the method1100, can increase the effect of the scaled perspective zoom. At operation1105, the interface engine615receives an input to resize the target feature, as discussed above. At operation1110, the scale engine620resizes the target feature according to the input. At operation1115, the scale engine620negatively scales the target feature so that the size of the target feature decreases as the client device moves or the background digitally moves, as discussed above. At operation1120, the stabilization engine625stabilizes the target feature in its location (e.g., the center of the one or more images) as the background moves.

FIG.12shows an example image1200for applying a scaled perspective zoom, according to some example embodiments. The image1200may be an image from a live video feed from which the one or more images capturing the scaled perspective zoom effect are generated. As illustrated, the image1200comprises a target feature1205, which is a man (e.g., head, neck, and shoulders of the man). As used herein, the depicted subject is the physical man while the target feature is feature data or image data that corresponds to the pixels used to depict the physical man. The objects of the image1200that are not part of the target feature1205are a background1210. As illustrated, the background1210depicts objects including the ground upon which pyramids sit, and a ceiling. Further displayed in the image1200is a mesh1215which the feature engine610has generated as part of the face detection in operation805inFIG.8.

FIG.13shows example images with the perspective zoom applied, according to some example embodiments. Images1300-1310are captured from top to bottom sequentially as part of a live feed by an image capture device of the client device102. The images1300-1310may be dynamically displayed on a display device of the client device102as they are captured. As illustrated in the example ofFIG.13, the target feature1205maintains the same size as the perspective of the background1210moves in the images1300-1310. In particular, for example, the grid lines of the ground and ceiling in the image1300approach the vanishing point more quickly than the grid lines of the ground and ceiling in the image1310. Further, the perspective change is apparent in the furthest pyramids, as they appear closer to the head (and vanishing point) in the image1300than in the image1305. As appreciated by one of ordinary skill in the art, the vanishing point is a far-off point in space (not depicted) that the gridlines tend to (e.g., the point at which parallel lines appear to intersect).

In the images1300-1310, the background1210may move due to the client device102physically moving closer to the depicted subject (e.g., the man corresponding to the target feature1205). Although only three images—e.g., image1300, image1305, and image1310—are shown as the one or more images capturing the scaled perspective zoom effect, it is to be appreciated that the one or more images may contain any number of sequential images captured as a video feed. The number of images can correspond to the frame rate of the client device and an amount of time that a record button is depressed on the client device. For example, if the client device records 30 frames per second, and the record button is depressed for five seconds as the client device moves closer to the physical man, then the number of images capturing the scaled perspective zoom is 150. In some example embodiments, the recording of the one or more images occurs automatically after the target feature is detected. Further, according to some example embodiments, the recording of the one or more images and/or the scaling of the target feature may be triggered by motion components1734of the client device102, as discussed in further detail with reference toFIG.17below.

FIG.14shows an example of shape detection, according to some example embodiments. As illustrated, an image1400includes a background1410and a cube1405, which is a physical object not yet identified as a target object. The user can use a user input, such as a gesture, to instruct the feature engine610to perform shape detection in an area indicated by the user input. For example, as indicated by dotted circles1415, the user uses two of his/her fingers to simultaneously tap on the cube1405to indicate to the feature engine610to perform shape detection in that area. In response to the gesture, the feature engine610performs shape detection (e.g., using edge detection, feature detection, or blob detection) to detect the shape or outline of the cube1405. In some example embodiments, a user can use his/her finger as a drawing tool to encircle an area on the display device around a shape to be detected. For example, the user may drag his/her finger around the cube1405as displayed on the screen of the client device102to indicate to the feature engine610to perform shape detection within the encircled area. In response to the drag gesture, the feature engine610can perform pixel analysis, color analysis, or other types of image feature detection to identify the cube1405as a target feature.

After the shape of the cube1405is detected, the feature engine610tracks the pixels that depict the cube1405as a target feature1425, as indicated by the bold black border around the cube1405in an image1420.

Further illustrated in the image1420is added imagery which can replace some or all of the background1410. In particular, the initial background1410, which was the physical background physically behind the cube1405, is replaced with added imagery1430(e.g., a replacement background). The added imagery1430can be computer generated. In the example illustrated in the image1420, the added imagery1430includes a complete background replacement image that completely replaces the initial background1410. For example, the background in the added imagery1430displays an open sky with no ceiling. According to some example embodiments, because the added imagery1430is computer generated, the perspective can more readily be changed to enable a scaled perspective zoom effect. For example, the scale of the target feature1425(corresponding to the physical cube1405) may be maintained while the perspective of the added imagery1430is zoomed out or zoomed in to create a change in perspective. Further, in some example embodiments, the replaced background is not computer generated imagery (CGI) but rather a pre-recorded sequence of a physical real world environment. In those example embodiments, the pre-recorded sequence can replace the background to make it appear as though the target feature is in the foreground of the pre-recorded sequence.

Further, as illustrated in the image1420, the added imagery1430can include one or more three-dimensional (3D) shapes, such as a cylinder1435. Other examples of three-dimensional added imagery include trees, buildings, cars, and other representations of real-world objects.

Further, according to some example embodiments, the added imagery1430includes one or more two-dimensional (2D) objects such as a plaque1440and a tower1445. In some example embodiments, when the client device102receives an instruction to perform a scaled perspective zoom, the enhancement engine635uses a position component1738(e.g., a GPS sensor) to determine the location of the client device102. Next, the enhancement engine635generates added imagery that is specific to the current geographic location of the client device102. For example, in the example illustrated, the client device102is in North Beach, San Francisco, California. Accordingly, the plaque1440may include text with the name of the area, “North Beach, SF”, and the tower1445may represent Coit Tower, a popular North Beach destination. In some example embodiments, the added imagery1430is pre-generated for different locations around the world and geo-fenced to those specific locations. For example, if the client device102is within 50 miles of Venice Beach, California, the added imagery1430can be a color sign that reads “Venice” and a cartoon sun in the simulated sky behind the cube1405.

FIG.15shows an example of body detection, according to some example embodiments. As illustrated, an image1500displays a girl1505who is holding a glass and touching her hat. The girl1505is a physical object that is not yet identified as a target feature. In response to a user input (e.g., operation710ofFIG.7triggering operation810ofFIG.8, tapping in the area of the image1500in which the girl1505is depicted), the feature engine610performs body detection to identify the girl1505as a target feature1515(denoted by shading of different styles) as illustrated in an image1550. As discussed above, in some example embodiments, the feature engine610implements a convolutional neural network to detect and segment different portions of the girl's body. For example, as illustrated, the target feature1515can include a hat segment1520, skin segment(s)1525(including both the face and hand areas), a clothing segment1530, and a hair segment1535. The different segments of the target feature1515can be used to apply different overlay filters (e.g., putting funny glasses over the girl), or can be used for scaling according to some example embodiments. For example, after the target feature1515is identified, the skin segment(s)1525may undergo positive scaling more quickly than the other segments, thereby resulting in a unique-looking (e.g., zany) scaled perspective zoom effect.

FIG.16is a block diagram illustrating an example software architecture1606, which may be used in conjunction with various hardware architectures herein described.FIG.16is a non-limiting example of a software architecture, and it will be appreciated that many other architectures may be implemented to facilitate the functionality described herein. The software architecture1606may execute on hardware such as a machine1700ofFIG.17that includes, among other things, processors1704, memory1714, and I/O components1718. A representative hardware layer1652is illustrated and can represent, for example, the machine1700ofFIG.17. The representative hardware layer1652includes a processing unit1654having associated executable instructions1604. The executable instructions1604represent the executable instructions of the software architecture1606, including implementation of the methods, components, and so forth described herein. The hardware layer1652also includes memory and/or storage modules memory/storage1656, which also have the executable instructions1604. The hardware layer1652may also comprise other hardware1658.

In the example architecture ofFIG.16, the software architecture1606may be conceptualized as a stack of layers where each layer provides particular functionality. For example, the software architecture1606may include layers such as an operating system1602, libraries1620, frameworks/middleware1618, applications1616, and a presentation layer1614. Operationally, the applications1616and/or other components within the layers may invoke application programming interface (API) calls1608through the software stack and receive a response in the form of messages1612. The layers illustrated are representative in nature and not all software architectures have all layers. For example, some mobile or special-purpose operating systems may not provide a frameworks/middleware1618, while others may provide such a layer. Other software architectures may include additional or different layers.

The operating system1602may manage hardware resources and provide common services. The operating system1602may include, for example, a kernel1622, services1624, and drivers1626. The kernel1622may act as an abstraction layer between the hardware and the other software layers. For example, the kernel1622may be responsible for memory management, processor management (e.g., scheduling), component management, networking, security settings, and so on. The services1624may provide other common services for the other software layers. The drivers1626are responsible for controlling or interfacing with the underlying hardware. For instance, the drivers1626include display drivers, camera drivers, Bluetooth® drivers, flash memory drivers, serial communication drivers (e.g., Universal Serial Bus (USB) drivers), Wi-Fi® drivers, audio drivers, power management drivers, and so forth depending on the hardware configuration.

The libraries1620provide a common infrastructure that is used by the applications1616and/or other components and/or layers. The libraries1620provide functionality that allows other software components to perform tasks in an easier fashion than by interfacing directly with the underlying operating system1602functionality (e.g., kernel1622, services1624, and/or drivers1626). The libraries1620may include system libraries1644(e.g., C standard library) that may provide functions such as memory allocation functions, string manipulation functions, mathematical functions, and the like. In addition, the libraries1620may include API libraries1646such as media libraries (e.g., libraries to support presentation and manipulation of various media formats such as MPEG4, H.264, MP3, AAC, AMR, JPG, or PNG), graphics libraries (e.g., an OpenGL framework that may be used to render 2D and 3D graphic content on a display), database libraries (e.g., SQLite that may provide various relational database functions), web libraries (e.g., WebKit that may provide web browsing functionality), and the like. The libraries1620may also include a wide variety of other libraries1648to provide many other APIs to the applications1616and other software components/modules.

The frameworks/middleware1618provide a higher-level common infrastructure that may be used by the applications1616and/or other software components/modules. For example, the frameworks/middleware1618may provide various graphic user interface (GUI) functions, high-level resource management, high-level location services, and so forth. The frameworks/middleware1618may provide a broad spectrum of other APIs that may be utilized by the applications1616and/or other software components/modules, some of which may be specific to a particular operating system1602or platform.

The applications1616include built-in applications1638and/or third-party applications1640. Examples of representative built-in applications1638may include, but are not limited to, a contacts application, a browser application, a book reader application, a location application, a media application, a messaging application, and/or a game application. The third-party applications1640may include an application developed using the ANDROID™ or IOS™ software development kit (SDK) by an entity other than the vendor of the particular platform, and may be mobile software running on a mobile operating system such as IOS™, ANDROID™, WINDOWS® Phone, or other mobile operating systems. The third-party applications1640may invoke the API calls1608provided by the mobile operating system (such as the operating system1602) to facilitate functionality described herein.

The applications1616may use built-in operating system functions (e.g., kernel1622, services1624, and/or drivers1626), libraries1620, and frameworks/middleware1618to create user interfaces to interact with users of the system. Alternatively, or additionally, in some systems interactions with a user may occur through a presentation layer, such as the presentation layer1614. In these systems, the application/component “logic” can be separated from the aspects of the application/component that interact with a user.

FIG.17is a block diagram illustrating components of a machine1700, according to some example embodiments, able to read instructions from a machine-readable medium (e.g., a machine-readable storage medium) and perform any one or more of the methodologies discussed herein. Specifically,FIG.17shows a diagrammatic representation of the machine1700in the example form of a computer system, within which instructions1710(e.g., software, a program, an application, an applet, an app, or other executable code) for causing the machine1700to perform any one or more of the methodologies discussed herein may be executed. As such, the instructions1710may be used to implement modules or components described herein. The instructions1710transform the general, non-programmed machine1700into a particular machine1700programmed to carry out the described and illustrated functions in the manner described. In alternative embodiments, the machine1700operates as a standalone device or may be coupled (e.g., networked) to other machines. In a networked deployment, the machine1700may operate in the capacity of a server machine or a client machine in a server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine1700may comprise, but not be limited to, a server computer, a client computer, a personal computer (PC), a tablet computer, a laptop computer, a netbook, a set-top box (STB), a personal digital assistant (PDA), an entertainment media system, a cellular telephone, a smartphone, a mobile device, a wearable device (e.g., a smart watch), a smart home device (e.g., a smart appliance), other smart devices, a web appliance, a network router, a network switch, a network bridge, or any machine capable of executing the instructions1710, sequentially or otherwise, that specify actions to be taken by the machine1700. Further, while only a single machine1700is illustrated, the term “machine” shall also be taken to include a collection of machines that individually or jointly execute the instructions1710to perform any one or more of the methodologies discussed herein.

The machine1700may include processors1704, memory/storage1706, and I/O components1718, which may be configured to communicate with each other such as via a bus1702. The memory/storage1706may include a memory1714, such as a main memory, or other memory storage, and a storage unit1716, both accessible to the processors1704such as via the bus1702. The storage unit1716and memory1714store the instructions1710embodying any one or more of the methodologies or functions described herein. The instructions1710may also reside, completely or partially, within the memory1714, within the storage unit1716, within at least one of the processors1704(e.g., within the processor's cache memory), or any suitable combination thereof, during execution thereof by the machine1700. Accordingly, the memory1714, the storage unit1716, and the memory of the processors1704are examples of machine-readable media.

The I/O components1718may include a wide variety of components to receive input, provide output, produce output, transmit information, exchange information, capture measurements, and so on. The specific I/O components1718that are included in a particular machine1700will depend on the type of machine. For example, portable machines such as mobile phones will likely include a touch input device or other such input mechanisms, while a headless server machine will likely not include such a touch input device. It will be appreciated that the I/O components1718may include many other components that are not shown inFIG.17. The I/O components1718are grouped according to functionality merely for simplifying the following discussion and the grouping is in no way limiting. In various example embodiments, the I/O components1718may include output components1726and input components1728. The output components1726may include visual components (e.g., a display such as a plasma display panel (PDP), a light-emitting diode (LED) display, a liquid-crystal display (LCD), a projector, or a cathode ray tube (CRT)), acoustic components (e.g., speakers), haptic components (e.g., a vibratory motor, resistance mechanisms), other signal generators, and so forth. The input components1728may include alphanumeric input components (e.g., a keyboard, a touch screen configured to receive alphanumeric input, a photo-optical keyboard, or other alphanumeric input components), point-based input components (e.g., a mouse, a touchpad, a trackball, a joystick, a motion sensor, or other pointing instruments), tactile input components (e.g., a physical button, a touch screen that provides location and/or force of touches or touch gestures, or other tactile input components), audio input components (e.g., a microphone), and the like.

In further example embodiments, the I/O components1718may include biometric components1730, motion components1734, environment components1736, or position components1738among a wide array of other components. For example, the biometric components1730may include components to detect expressions (e.g., hand expressions, facial expressions, vocal expressions, body gestures, or eye tracking), measure biosignals (e.g., blood pressure, heart rate, body temperature, perspiration, or brain waves), identify a person (e.g., voice identification, retinal identification, facial identification, fingerprint identification, or electroencephalogram-based identification), and the like. The motion components1734may include acceleration sensor components (e.g., accelerometer), gravitation sensor components, rotation sensor components (e.g., gyroscope), and so forth. The environment components1736may include, for example, illumination sensor components (e.g., photometer), temperature sensor components (e.g., one or more thermometers that detect ambient temperature), humidity sensor components, pressure sensor components (e.g., barometer), acoustic sensor components (e.g., one or more microphones that detect background noise), proximity sensor components (e.g., infrared sensors that detect nearby objects), gas sensors (e.g., gas sensors to detect concentrations of hazardous gases for safety or to measure pollutants in the atmosphere), or other components that may provide indications, measurements, or signals corresponding to a surrounding physical environment. The position components1738may include location sensor components (e.g., a GPS receiver component), altitude sensor components (e.g., altimeters or barometers that detect air pressure from which altitude may be derived), orientation sensor components (e.g., magnetometers), and the like.

Communication may be implemented using a wide variety of technologies. The I/O components1718may include communication components1740operable to couple the machine1700to a network1732or devices1720via a coupling1722and a coupling1724respectively. For example, the communication components1740may include a network interface component or other suitable device to interface with the network1732. In further examples, the communication components1740may include wired communication components, wireless communication components, cellular communication components, Near Field Communication (NFC) components, Bluetooth® components (e.g., Bluetooth® Low Energy), Wi-Fi® components, and other communication components to provide communication via other modalities. The devices1720may be another machine or any of a wide variety of peripheral devices (e.g., a peripheral device coupled via a Universal Serial Bus (USB)).

Moreover, the communication components1740may detect identifiers or include components operable to detect identifiers. For example, the communication components1740may include Radio Frequency Identification (RFID) tag reader components, NFC smart tag detection components, optical reader components (e.g., an optical sensor to detect one-dimensional barcodes such as Universal Product Code (UPC) barcode, multi-dimensional barcodes such as Quick Response (QR) code, Aztec code, Data Matrix, Dataglyph, MaxiCode, PDF417, Ultra Code, UCC RSS-2D barcode, and other optical codes), or acoustic detection components (e.g., microphones to identify tagged audio signals). In addition, a variety of information may be derived via the communication components1740, such as location via Internet Protocol (IP) geolocation, location via Wi-Fi® signal triangulation, location via detecting an NFC beacon signal that may indicate a particular location, and so forth.

Glossary

“CARRIER SIGNAL” in this context refers to any intangible medium that is capable of storing, encoding, or carrying instructions for execution by the machine, and includes digital or analog communications signals or other intangible media to facilitate communication of such instructions. Instructions may be transmitted or received over the network using a transmission medium via a network interface device and using any one of a number of well-known transfer protocols.

“CLIENT DEVICE” in this context refers to any machine that interfaces to a communications network to obtain resources from one or more server systems or other client devices. A client device may be, but is not limited to, a mobile phone, desktop computer, laptop, PDA, smartphone, tablet, ultrabook, netbook, multi-processor system, microprocessor-based or programmable consumer electronics system, game console, set-top box, or any other communication device that a user may use to access a network.

“COMMUNICATIONS NETWORK” in this context refers to one or more portions of a network that may be an ad hoc network, an intranet, an extranet, a virtual private network (VPN), a local area network (LAN), a wireless LAN (WLAN), a wide area network (WAN), a wireless WAN (WWAN), a metropolitan area network (MAN), the Internet, a portion of the Internet, a portion of the Public Switched Telephone Network (PSTN), a plain old telephone service (POTS) network, a cellular telephone network, a wireless network, a Wi-Fi® network, another type of network, or a combination of two or more such networks. For example, a network or a portion of a network may include a wireless or cellular network and the coupling may be a Code Division Multiple Access (CDMA) connection, a Global System for Mobile communications (GSM) connection, or another type of cellular or wireless coupling. In this example, the coupling may implement any of a variety of types of data transfer technology, such as Single Carrier Radio Transmission Technology (1×RTT), Evolution-Data Optimized (EVDO) technology, General Packet Radio Service (GPRS) technology, Enhanced Data rates for GSM Evolution (EDGE) technology, third Generation Partnership Project (3GPP) including 3G, fourth generation wireless (4G) networks, Universal Mobile Telecommunications System (UMTS), High-Speed Packet Access (HSPA), Worldwide Interoperability for Microwave Access (WiMAX), Long-Term Evolution (LTE) standard, others defined by various standard-setting organizations, other long-range protocols, or other data transfer technology.

“EMPHEMERAL MESSAGE” in this context refers to a message that is accessible for a time-limited duration. An ephemeral message may be a text, an image, a video, and the like. The access time for the ephemeral message may be set by the message sender. Alternatively, the access time may be a default setting or a setting specified by the recipient. Regardless of the setting technique, the message is transitory.

“MACHINE-READABLE MEDIUM” in this context refers to a component, a device, or other tangible media able to store instructions and data temporarily or permanently and may include, but is not limited to, random-access memory (RAM), read-only memory (ROM), buffer memory, flash memory, optical media, magnetic media, cache memory, other types of storage (e.g., Erasable Programmable Read-Only Memory (EPROM)), and/or any suitable combination thereof. The term “machine-readable medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, or associated caches and servers) able to store instructions. The term “machine-readable medium” shall also be taken to include any medium, or combination of multiple media, that is capable of storing instructions (e.g., code) for execution by a machine, such that the instructions, when executed by one or more processors of the machine, cause the machine to perform any one or more of the methodologies described herein. Accordingly, a “machine-readable medium” refers to a single storage apparatus or device, as well as “cloud-based” storage systems or storage networks that include multiple storage apparatus or devices. The term “machine-readable medium” excludes signals per se.

“COMPONENT” in this context refers to a device, a physical entity, or logic having boundaries defined by function or subroutine calls, branch points, APIs, or other technologies that provide for the partitioning or modularization of particular processing or control functions. Components may be combined via their interfaces with other components to carry out a machine process. A component may be a packaged functional hardware unit designed for use with other components and a part of a program that usually performs a particular function of related functions. Components may constitute either software components (e.g., code embodied on a machine-readable medium) or hardware components. A “hardware component” is a tangible unit capable of performing certain operations and may be configured or arranged in a certain physical manner. In various example embodiments, one or more computer systems (e.g., a standalone computer system, a client computer system, or a server computer system) or one or more hardware components of a computer system (e.g., a processor or a group of processors) may be configured by software (e.g., an application or application portion) as a hardware component that operates to perform certain operations as described herein. A hardware component may also be implemented mechanically, electronically, or any suitable combination thereof. For example, a hardware component may include dedicated circuitry or logic that is permanently configured to perform certain operations. A hardware component may be a special-purpose processor, such as a Field-Programmable Gate Array (FPGA) or an Application-Specific Integrated Circuit (ASIC). A hardware component may also include programmable logic or circuitry that is temporarily configured by software to perform certain operations. For example, a hardware component may include software executed by a general-purpose processor or other programmable processor. Once configured by such software, hardware components become specific machines (or specific components of a machine) uniquely tailored to perform the configured functions and are no longer general-purpose processors. It will be appreciated that the decision to implement a hardware component mechanically, in dedicated and permanently configured circuitry, or in temporarily configured circuitry (e.g., configured by software) may be driven by cost and time considerations. Accordingly, the phrase “hardware component” (or “hardware-implemented component”) should be understood to encompass a tangible entity, be that an entity that is physically constructed, permanently configured (e.g., hardwired), or temporarily configured (e.g., programmed) to operate in a certain manner or to perform certain operations described herein. Considering embodiments in which hardware components are temporarily configured (e.g., programmed), each of the hardware components need not be configured or instantiated at any one instance in time. For example, where a hardware component comprises a general-purpose processor configured by software to become a special-purpose processor, the general-purpose processor may be configured as respectively different special-purpose processors (e.g., comprising different hardware components) at different times. Software accordingly configures a particular processor or processors, for example, to constitute a particular hardware component at one instance of time and to constitute a different hardware component at a different instance of time. Hardware components can provide information to, and receive information from, other hardware components. Accordingly, the described hardware components may be regarded as being communicatively coupled. Where multiple hardware components exist contemporaneously, communications may be achieved through signal transmission (e.g., over appropriate circuits and buses) between or among two or more of the hardware components. In embodiments in which multiple hardware components are configured or instantiated at different times, communications between or among such hardware components may be achieved, for example, through the storage and retrieval of information in memory structures to which the multiple hardware components have access. For example, one hardware component may perform an operation and store the output of that operation in a memory device to which it is communicatively coupled. A further hardware component may then, at a later time, access the memory device to retrieve and process the stored output. Hardware components may also initiate communications with input or output devices, and can operate on a resource (e.g., a collection of information). The various operations of example methods described herein may be performed, at least partially, by one or more processors that are temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors may constitute processor-implemented components that operate to perform one or more operations or functions described herein. As used herein, “processor-implemented component” refers to a hardware component implemented using one or more processors. Similarly, the methods described herein may be at least partially processor-implemented, with a particular processor or processors being an example of hardware. For example, at least some of the operations of a method may be performed by one or more processors or processor-implemented components. Moreover, the one or more processors may also operate to support performance of the relevant operations in a “cloud computing” environment or as a “software as a service” (SaaS). For example, at least some of the operations may be performed by a group of computers (as examples of machines including processors), with these operations being accessible via a network (e.g., the Internet) and via one or more appropriate interfaces (e.g., an API). The performance of certain of the operations may be distributed among the processors, not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the processors or processor-implemented components may be located in a single geographic location (e.g., within a home environment, an office environment, or a server farm). In other example embodiments, the processors or processor-implemented components may be distributed across a number of geographic locations.

“PROCESSOR” in this context refers to any circuit or virtual circuit (a physical circuit emulated by logic executing on an actual processor) that manipulates data values according to control signals (e.g., “commands”, “op codes”, “machine code”, etc.) and which produces corresponding output signals that are applied to operate a machine. A processor may, for example, be a Central Processing Unit (CPU), a Reduced Instruction Set Computing (RISC) processor, a Complex Instruction Set Computing (CISC) processor, a Graphics Processing Unit (GPU), a Digital Signal Processor (DSP), an ASIC, a Radio-Frequency Integrated Circuit (RFIC), or any combination thereof. A processor may further be a multi-core processor having two or more independent processors (sometimes referred to as “cores”) that may execute instructions contemporaneously.

“TIMESTAMP” in this context refers to a sequence of characters or encoded information identifying when a certain event occurred, for example giving date and time of day, sometimes accurate to a small fraction of a second.

A portion of the disclosure of this patent document contains material that is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent files or records, but otherwise reserves all copyright rights whatsoever. The following notice applies to the software and data as described below and in the drawings that form a part of this document: Copyright 2017, SNAP INC., All Rights Reserved.