WO2013063745A1

WO2013063745A1 - On-demand video cut service

Info

Publication number: WO2013063745A1
Application number: PCT/CN2011/081567
Authority: WO
Inventors: Sailesh Kumar Sathish; Jilei Tian
Original assignee: Nokia Corporation
Priority date: 2011-10-31
Filing date: 2011-10-31
Publication date: 2013-05-10
Also published as: CN104025081A

Abstract

Methods and apparatus, including computer program products, are provided for a video cut service. The method may include receiving one or more search parameters to search metadata associated with one or more videos, wherein the metadata comprises information from one or more sources and context information, or a combination thereof, derived from the metadata; receiving one or more model parameters to form a composite video based at least in part on the received one or more search parameters; concatenating, based on at least the one or more model parameters, one or more candidate videos to form the composite video; and providing the composite video. The concatenation may be performed based on parameters supplied by a user and/or automatically. Related apparatus, systems, methods, and articles are also described.

Description

ON-DEMAND VIDEO CUT SERVICE FIELD

[0001 ] The subject matter described herein relates to generating personalized videos on demand according to user's need.

BACKGROUND

[0002] Videos have become commonplace today on the Internet. Indeed, almost every type of website has video content. For example, news organizations, such as for example CNN, have searchable news stories including videos that can be streamed to a desktop computer, a cell phone, and the like. Moreover, many websites now allow user generated content to be uploaded and shared. For example, social networking websites and video sharing websites allow users to upload videos, annotate the videos with metadata and then share the videos with the general public or a select group of friends. Although video content is now prolific on the Internet, searching videos may present a challenge based on the sheer volume of available video and technical complexities associated with video searching.

SUMMARY

[0003] Methods and apparatus, including computer program products, are provided for an on-demand video cut service. For some example embodiments, there is provided a method. The method may include processing one or more search parameters to search metadata associated with one or more videos, wherein the metadata comprises information from one or more sources and context information, or a combination thereof, derived from the metadata; and processing one or more model parameters to form a composite video based at least in part on the processing of the one or more search parameters.

[0004] In some variations of some of the embodiments disclosed herein, one or more of the following may be included. The metadata may include one or more of information obtained from a website hosting the one or more videos, a first information from a first user that generated the one or more videos, and a second information from a second user other than the user that generated the one or more videos, or a combination thereof. The metadata may include information derived from the metadata associated with the one or more videos. The metadata may include context information derived from location information associated with the one or more videos. The metadata may include context information derived from information about a user associated with the one or more videos, wherein the information about the user is obtained from a second website other than a first website hosting the one or more videos. The metadata may include one or more of a multimedia metadata and a textual annotation provided by a user. The composite video may be received after the search of the metadata, wherein the search is performed by comparing the one or more search parameters with one or more topics characterizing the metadata. The one or more candidate videos may be identified based on at least a match of the one or more search parameters and one or more topics characterizing the metadata. The one or more candidate videos identified by the search may be concatenated. A user interface may be generated to enable modifying the one or more model parameters, wherein the modification causes another composite video to be received. The one or more search parameters may be provided to enable the search. The one or more model parameters may be provided to enable formation of the composite video. For various example embodiments, the following may be applicable: an apparatus comprising means for performing a method of any of claims 1 -12; wherein the apparatus comprises a user equipment; and a computer-readable storage medium carrying one or more sequences of one or more instructions which, when executed by one or more processors, cause an apparatus to perform at least a method of any of claims 1 -12.

[0005] For some example embodiments, there is also provided a method. The method may include receiving one or more search parameters to search metadata associated with one or more videos, wherein the metadata comprises information from one or more sources and context information, or a combination thereof, derived from the metadata; receiving one or more model parameters to form a composite video based at least in part on the received one or more search parameters; concatenating, based on at least the one or more model parameters, one or more candidate videos to form the composite video; and providing the composite video.

[0006] In some variations of some of the embodiments disclosed herein, one or more of the following may be included. The metadata associated with one or more videos may be searched based one or more search parameters received from a user equipment. At least one other model parameter may be received from the user equipment to cause at least another composite video to be formed. The metadata may include one or more of information obtained from a website hosting the one or more videos, information from a user that generated the one or more videos, and information from a second user other than the user that generated the one or more videos. The metadata may include information derived from the metadata associated with the one or more videos. The metadata may include context information derived from location information associated with the one or more videos. The metadata may include context information derived from information about a user associated with the one or more videos, wherein the information about the user is obtained from a second website other than a first website hosting the one or more videos. The metadata may include one or more of a multimedia metadata and a textual annotation provided by a user. At least one of the one or more candidate videos may be identified by searching topics determined from the metadata associated with the one or more videos. The searching may be performed by at least comparing the one or more search parameters with one or more topics characterizing the metadata. For various example embodiments, the following may be applicable: an apparatus comprising means for performing a method of any of claims 16-25; wherein the apparatus comprises a server coupled to the Internet; and a computer-readable storage medium carrying one or more sequences of one or more instructions which, when executed by one or more processors, cause an apparatus to perform at least a method of any of claims 16-25.

[0007] The above-noted aspects and features may be implemented in systems, apparatus, methods, and/or articles depending on the desired configuration. The details of one or more variations of the subject matter described herein are set forth in the accompanying drawings and the description below. Features and advantages of the subject matter described herein will be apparent from the description and drawings, and from the claims.

DESCRIPTION OF DRAWINGS

[0008] In the drawings,

[0009] FIG. 1 depicts a block diagram of a system for generating a video cut in accordance with some exemplary embodiments; [0010] FIG. 2 depicts an example of a user interface for entering search parameters and model parameters for generating a video cut video in accordance with some exemplary embodiments;

[001 1 ] FIG. 3 depicts an example search in accordance with some exemplary embodiments;

[0012] FIG. 4 depicts a block diagram of another system for generating a video cut in accordance with some exemplary embodiments;

[0013] FIG. 5 depicts an example of a process for generating a video cut in accordance with some exemplary embodiments;

[0014] FIG. 6 depicts an example of another process for generating a video cut in accordance with some exemplary embodiments;

[0015] FIG. 7 depicts an example of a user equipment in accordance with some exemplary embodiments; and

[0016] FIG. 8 depicts an example of a server in accordance with some exemplary embodiments.

[0017] Like labels are used to refer to same or similar items in the drawings.

DETAILED DESCRIPTION

[0018] FIG. 1 is a simplified functional block diagram of a system 100 in accordance with some exemplary embodiments. The system 100 may include at least one server, such as for example video server 190, configured to provide videos, such as for example video content 192A-C and metadata 194A-C describing the video content 192A-C.

The video content 192A-C may include videos from a variety of sources. For example, the video content 192A-C may include a portion of video content generated by a user and then posted to a website, such as for example a social networking website, a video sharing website, and the like. Moreover, the video content 192A-C may include video content from traditional website providers of video content, such as for example news websites, entertainment websites, sports websites, television broadcaster websites, and the like.

[0019] In addition, the video content 192A-C may be associated with metadata associated with the video content. This metadata may be obtained from the source of the video content, other entities viewing the website, and/or generated by system 100 using the video analyzer 195, which may derive metadata including context information from the video and/or from the set of metadata associated with the video or a user associated with the video. For example, video content 192A may be received at video server 190 from a social networking site (which is a source of the video) and metadata 194A may also be received in the form of the posting date of the video, the identity of the poster (or generator) of the video, the location of where the video is taken, user provided tags relating to topics which may be included in the video, and textual comments describing the video. Moreover, the metadata may include information from a variety of users viewing the video, such as for example posts commenting on the video.

[0020] In some exemplary embodiments, system 100 may analyze the video and/or the metadata associated with the video using video analyzer 195. The video analyzer 195 may generate, based on the analysis, metadata for any video stored at video server 190, and may determine context information for the video. For example, the video analyzer 195 may determine that the video 192A was obtained at a concert based on context information obtained from a social networking website where the video is posted or another website associated with the user generating video 192A (e.g., metadata obtained from a user's Twitter account indicating that, at the time when then video 192A was created, the user posted "@ AC/DC concert"). In this example, video analyzer 195 may enhance the metadata 194A with the semantic information tag "concert."

[0021 ] In some exemplary implementations, latent characteristics of video 192A may be determined by analyzer 195. For example, video 192A taken by user equipment 114A may include location information (e.g., global positioning information, cell identifier, and the like), which may be used to derive acceleration information for the video. Given the acceleration information, the analyzer 195 may derive that the user (and thus the video 192A taken by that user) was in a car, a bus, a boat, and the like. And, using just the location information, the analyzer 195 may derive that the user and thus video 194A was taken at a shopping center, a tourist attraction, a restaurant, and the like.

[0022] Although the previous examples describe specific instances of context information derived from latent aspects of the user, the video 192A, and/or the set of metadata 194A associated with the video 192A, this context information is merely an example as other types of context information may be derived as well and associated as metadata 194A for video 192A at video server 190.

[0023] In some exemplary embodiments, the metadata 194A-C may include multimedia metadata including images, textual annotations provided by a user, and/or portions of video. In some exemplary embodiments, metadata from a variety of sources is combined and stored in video server 190, and metadata including contextual information may also be derived by analyzer 195. Moreover, this combined set of metadata may include derived latent characteristics that may be presented as search parameters (or topics) during a search 198B and/or as model parameters to concatenate 198D videos using a cut model 198C. In some exemplary embodiments, the model parameters of the cut model 198C may be adjusted by a user to create the video cut comprising one or more video segments returned by the search 198B. The search 198B, cut model 198C, and concatenation 198D are described further below.

[0024] In some exemplary embodiments, the metadata, such as for example metadata 194A-C, may be distributed topically. In this example, when search parameters are used to search 198B through the metadata 194A-C, the search parameters are compared to a plurality of topics distributed across the metadata 194A-C. The searching 198B may then match one or more topics (e.g., a distribution of topics across the metadata 194A-C) to the search parameters. A matching topic may thus correspond to metadata mapped to a corresponding video clip. For example, a video 192B may include metadata with a distribution of topics, such as for example January 1 , 2011 , news, sports, a user identity (e.g., a first name and surname), and location information. In this example, a search parameter for news events on January 1 , 2011 would match two of the topics, and thus the video 192B would likely be selected given the search parameters. Although the previous example describes a simple search and matching process, other search approaches may be used to search the metadata 194A-C for the videos 192A-C including cost-optimization-based search algorithms, index-based searches, latent semantic indexing and searching, topic models, and the like. To further illustrate the use of a topic model, it provides a mathematical framework to model the semantics of the metadata at the video server 190 including any documents, words, tags, and/or any other information which may be associated with videos 192A-C. Moreover, topic modeling may be used to model text-based semantics, such as topics, category, interest, and the like. In some implementations, topic models may be better suited for semantic searching at 198B, when compared to simple key word matching, although both approaches, or a combination thereof may be used. [0025] The system 100 further includes a video cut generator 198A including the searcher 198B, the cut model 198C, and the concatenator 198D. In some exemplary embodiments, the video cut generator 198A may search for videos in accordance with search parameters provided by user equipment 114A, select one or more candidate videos, propose to user equipment 114A one or more cut models describing how to combine the candidate videos, and combine, based on the cut model, the candidate videos into a single cut (referred to herein as a video cut. The video cut thus represents a montage of videos assembled based on the cut model 198C and the model parameters provided by the user/user equipment.

[0026] To illustrate by way of an example, a user at user equipment 114A may make a video cut of the unveiling of the BMW 735 on a given day. In this example, the video cut generator 198A may receive a command to "build a review video clip of BMW 735 on January 1 , 2010." The search module 198B searches, based on the search parameters "BMW 735 videos" and "January 1 , 2010," through one or more servers including video server 190 and searches through metadata including metadata 194A-C. The search results may include one or more candidate videos. At this point, the cut model 198C may be used to combine the candidate videos returned by the search 198B. For example, the cut model 198C may allow a user to select one or more model parameters, such as for example a quality parameter, a beat parameter, a location parameter, a video duration parameter, and the like, or any combination thereof. In the case of a beat parameter, the cut model 198C may concatenate videos based on the audio beat in the videos by detecting the first beat, the second beat, and so forth, such that when a change in beat is detected, focus changes to a different video, a different angle of a video, or to an entirely new video clip. [0027] Returning the previous example of the BMW debut, the metadata 194A-C may be considered rich given that it includes metadata from a variety of sources and/or has been augmented by analyzer 195. As such, any of the search parameters and/or model parameters may be used in the cut model 198C to combine the returned candidate videos. For example, the cut model 198C may propose a combination based on how well the videos match "BMW 735" and "January 1 , 2010," as well as other topics derived from the metadata 194A-C, such as for example length of video, location information, derived user context information, and the like.

[0028] The concatenator 198D then proposes, based on the cut model 198C, to user equipment 114A (or a user at user equipment 114A) a video cut comprising one or more candidate video clips returned by the search 198D. In some exemplary

embodiments, the cut model 198C may be varied by the user at user equipment 114A during the search, while in other embodiments, the cut model 198C may be set as a default cut model 198C, so that it cannot be readily altered by the user.

[0029] To illustrate by way of another example, a user at user equipment 114A may make a video cut including portions of videos (e.g., cuts or clips) of all major events that happened on a child's birthday either globally, within a region, and/or given a semantic constraint. For example, the on demand video can be generated by concatenating all video clips having the event "celebrate a child's birthday in Helsinki" and "videos about party with friends in the campus, other than at home." In this example, the semantic constraints are "party with friends," "campus other than home," and the like. In the birthday example, the video cut generator 198A may receive a command to "build a review video clip of news on January 1 , 2000 anywhere in the world." After some searching, the cut model 198C may propose additional model parameters to narrow the combined videos, such as for example location where the video originated, length of the video, quality (e.g., high definition, standard definition, etc.), a maximum quantity of videos to concatenate to form the video cut, whether any preference should be given to video's obtained from friends or friends of friends, and the like. The concantenator 198D may then concatenate based on the model parameters, and provide to user interface 114A a video cut comprising a plurality of portions of videos. Returning to the review clip example above, the model parameters may specify a location of anywhere, a maximum quantity of videos to

concatenate of 3, and a 3-minute length/duration limit for each video. In this example, the concantenator 198D may generate a 9-minute video cut consisting of three 3-minite videos of news dated January 1 , 2000.

[0030] In some exemplary embodiments, the video cut generator 198A and video server 190 may be coupled to a network 160, which may be further coupled to wireless access networks, such as for example wireless access network 165A. For example, network 160 may include one or more networks, such as for example the Internet, access to the Internet Protocol (IP) Multimedia Subsystem, and backhaul access to network elements of the public land mobile network.

[0031 ] The wireless access network 165A may, in some exemplary embodiments, represent wireless networks. For example, the wireless access network 165A may provide coverage areas served by base stations of a public land mobile network, although other types of wireless networks, such as for example Wi-Fi networks and Wi-Fi wireless access points may be implemented as well. The wireless network may, in some exemplary embodiments, comprise mobile devices. When this is the case, a user can search videos from other user's mobile wireless devices (e.g., over local radio connection). In some exemplary embodiments, the wireless devices may install an application to enable the search of videos and/or their metadata, or the like.

[0032] The user equipment, such as for example user equipment 114A, may be implemented as a mobile wireless device, although at any given time the user equipment may be stationary as well. The user equipment may be referred to as, for example, devices, mobile stations, mobile units, subscriber stations, wireless terminals, terminals, tablets, and/or any other wireless device. Moreover, the user equipment may also be implemented as, for example, a wireless handheld device, a wireless plug-in accessory, or the like. For example, the user equipment may take the form of a wireless phone, a computer with a wireless connection to a network, or the like. In some instances, the user equipment may include one or more of the following: at least one processor, at least one computer-readable storage medium (e.g., memory, storage, and the like), a user interface, a radio access mechanism, and a video cut application 198. In some exemplary embodiments, the user equipment may include, or be coupled to, a video camera.

[0033] The video cut application 198 may be implemented as an application, a plug-in, an applet, and/or incorporated into another application, such as for example a social networking application. Moreover, the video cut application 198 may be configured to allow entering one or more search parameters and/or model parameters for the videos (also referred to herein as clips, segments, and/or portions of videos) to be searched for and concatenated into a video cut. The video cut application 198 may also present the concatenated videos at a user interface of the user equipment 114A.

[0034] FIG. 2 depicts an example of a user interface 200 generated by video cut application 198. The user interface 200 is configured so that a user can enter a variety of search parameters, such as for example search tags 205, dates 210, and location 215, which are provided (e.g., sent) by user equipment 114A to video cut generator 198A.

Moreover, the user interface 200 may include additional model parameters, which may be used by the cut model 198C to concatenate the candidate videos returned by the search 198B. For example, the length of video 220, maximum number of videos to concatenate 222, sources of videos 226, and whether a preference should be given to videos from friends or friends of friends 228 may be entered at user interface 200. Moreover, the combined video output of the concatenator 198D may be named at 224 and provided as the video cut to user equipment 114A. The user interface 200 may also allow login to other websites 229, such as for example Nokia services (e.g., maps, store, music, etc.), Facebook, and the like to allow access to video content at those websites.

[0035] FIG. 3 depicts an example of a search plan implemented by searcher 198B consistent with some exemplary embodiments. Referring to FIG. 3, the searcher 198B searches through video server 190 including video content 310 based on the requirements 305 provided at user interface 200 (e.g., search parameters, such as for example search tags 205, date interval 210, and location 215). For each of the

requirements, the searcher 198B selects a clip 310 based on a cost function 350 used to drive a search algorithm, such as for example a best-first search algorithm. Each of the selected clips 335 including any metadata (labeled annotations) 340 are provided to the concatenator 198D which combines the candidate clips 335 based on the cut model 198C.

[0036] FIG. 4 depicts a system 1000 in accordance with some exemplary embodiments. The system 1000 includes some features similar to those described with respect to system 100, but further depicts an implementation with a public land mobile network. [0037] Referring to FIG. 4, the video server 190 and video cut generator 198A may be coupled via network 160 to a base station 110. The base station 110 may be capable of communicating with wireless devices, such as for example user equipment 114A-C within the coverage area 112A. In the example of FIG. 4, user equipment 114D is not within the coverage area 112A, but instead within coverage area 112B, so user equipment 114D would be serviced by another base station.

[0038] The system 1000 may include access links, such as for example access links 122A-B, between the base station and the user equipment. The access links 122A-B may also include a downlink, such as for example downlinks 116A and 116B, for transmitting from the base station 110 to a corresponding user equipment. The access links 122A-B may also include an uplink, such as for example uplinks 126A and 126B, for transmitting from the user equipment to the base station. Ad hoc links 122C may link user equipment as well.

[0039] In some implementations, the base station 110 may be configured as an evolved Node B (eNB) type base station consistent with standards, including the Long Term Evolution (LTE)/LTE-Advanced standards, and any subsequent additions or revisions to these and other 3GPP series of standards (collectively referred to as LTE standards), although the base station may be implemented in accordance with other standards and technologies as well. Although the base station 110 is described as an eNB base station, the base station 110 may be configured in other ways as well and include, for example, cellular base station transceiver subsystems, gateways, access points, radio frequency (RF) repeaters, frame repeaters, nodes, servers, websites, and access to other networks. For example, base station 110 may have wired and/or wireless backhaul links including network/internet connections to other network nodes, such as for example other base stations, a radio network controller, a core network, a serving gateway, a mobility management entity, a serving GPRS (general packet radio service) support node, location servers, servers, websites, and the like.

[0040] Moreover, although base station 110 is described as a cellular, eNB base station, base station 110 may also be implemented as a wireless access point, such as for example a Wi-Fi wireless access point. When base station 110 is implemented as a Wi-Fi wireless access point, the uplinks and downlinks between the wireless access point and the user equipment 114A-C may be implemented as links configured in accordance with, for example, Wi-Fi, WiGig, and any wireless local area network standard.

[0041 ] Although FIG. 4 depicts a single base station 110 (or wireless access point), two coverage areas 112A-B, and four user equipment 114A-D, other quantities of base stations/wireless access points, coverage areas, and user equipment may be implemented as well.

[0042] FIG. 5 depicts an example process 500 for generating a video cut in accordance with some exemplary embodiments. The process 500 may be implemented at user equipment, such as for example user equipment 114A-D. The description of process 500 also refers to FIGs. 1 , 2, and 4.

[0043] At 560, at least one search parameter may be provided in accordance with some exemplary embodiments. For example, user equipment 114A may provide at least one search parameter to the video cut generator 198A. Moreover, the at least one search parameter may include one or more of the following: one or more alphanumeric tags 205, a date (or date range) 210, and a location (or region) 215. For example, a user may enter "Rugby Sevens highlights" (at 205), September 2011 (at 210), and New Zealand (at 215). These search parameters are then provided by the user equipment 114A to video cut generator 198A for searching 198B of videos 192A-C including metadata 194A-C. Although the previous example provided examples of search parameters, these are merely examples as other search parameters may be used as well.

[0044] At 562, at least one model parameter may be provided in accordance with some exemplary embodiments. For example, user equipment 114A may provide at least one model parameter to the video cut generator 198A. Moreover, the at least one model parameter may include one or more of the following: length of video (at 220), a maximum quantity of videos to concatenate (at 222), whether any preferences should be given to videos generated by friends and/or friends of friends (at 228), and/or any designated or preferred sources of videos (at 226). For example, a user may enter 2 minutes (at 220), 5 as the maximum quantity of video cuts to concatenate (at 222), yes regarding preferences to videos generated by friends and/or friends of friends (at 228), and designate a website as preferred sources of videos (at 226). These model parameters are then provided by the user equipment 114A to video cut generator 198A to enable proposing, based on the model parameters, a video cut consisting of candidate videos identified by search 198B using the parameters of 560. The cut model 198C in this example is thus defined by the set of model parameters received from user equipment 114A. Although the previous example provided examples of model parameters, these are merely examples as other model parameters may be used as well.

[0045] At 564, the concatenated video cut is received at the user equipment in accordance with some exemplary embodiments. Returning to the previous example, a video cut of New Zealand's Rugby Sevens highlight videos during the month of September 2011 may be formed. The video cut may include a montage of five 2-minute videos, which were gathered from a designated website, and some of which were obtained from friends/friends of friends.

[0046] In some exemplary embodiments, the video cut application 198 may present a page at a user interface of user equipment 114A to allow modifying one or more of the search parameters (see, e.g., 560) and/or model parameters (see, e.g., 562). If these parameters are modified, the video cut generator 198A may then re-execute 564, providing thus another video cut based on the new parameters.

[0047] FIG. 6 depicts an example process 600 for generating a video cut in accordance with some exemplary embodiments. The process 600 may be implemented at a server, such as for example video cut generator 198A. The description of process 600 also refers to FIGs. 1 , 2, and 4.

[0048] At 660, at least one search parameter may be received in accordance with some exemplary embodiments. For example, the video cut generator 198A may receive from user equipment 114A at least one search parameter. Moreover, the at least one search parameter may include one or more of the following: one or more

alphanumeric tags 205, a date (or date range) 210, and a location (or region) 215. For example, a user may enter "Rugby Sevens highlights" (at 205), September 2011 (at 210), and New Zealand (at 215). The search parameters may be used by the video cut generator 198A to search videos 192A-C including metadata 194A-C (which may include metadata from a variety of sources and contextual information, as well as derived latent characteristics as described above). Although the previous example provided examples of search parameters, these are merely examples as other search parameters may be used as well. [0049] At 662, at least one model parameter may be received in accordance with some exemplary embodiments. For example, the video cut generator 198A may receive from user equipment 114A at least one model parameter. The at least one model parameter may include one or more of the following: length of video (at 220), a maximum quantity of videos to concatenate (at 222), whether any preferences should be given to videos generated by friends and/or friends of friends (at 228), and any designated or preferred sources of videos (at 226). For example, a user may enter 2 minutes (at 220), five as the maximum quantity of video cuts to concatenate (at 222), yes regarding preferences to videos generated by friends and/or friends of friends (at 228), and designate a website as preferred sources of videos (at 226). These model parameters are then provided by the user equipment 114A to video cut generator 198A to enable proposing, based on the model parameters, a video cut consisting of candidate videos identified by a search 198B using the parameters of 660. Although the previous example provided examples of model parameters, these are merely examples as other model parameters may be used as well.

[0050] At 664, the candidate videos found by the search at 662 are

concatenated based on the model parameters of 662 in accordance with some exemplary embodiments. Returning to the previous example, video cut generator 198A may concatenate, based on a cut model 198C including model parameters, five 2-minute videos, which were gathered from designated websites, and some of which were obtained from friends/friends of friends to form the video cut of New Zealand's Rugby Sevens highlight videos during the month of September 2011 .

[0051 ] At 666, the video cut video is provided in accordance with some exemplary embodiments. For example, the video cut generator 198A may send the video cut formed at 664 to user equipment 114A and/or video cut application 198 for presentation at a user interface.

[0052] FIG. 7 depicts an exemplary user equipment 700, which may be implemented at one or more of user equipment 114A-D. The user equipment may include one or more antennas 720 coupled to radio interface 740. The radio interface 740 may include one or more interfaces to other devices and/or networks, such as for example internet access provided via wireless access points, cellular networks including base stations, and the like. The radio interface 740 may include other components, such as for example filters, converters (e.g., digital-to-analog converters and the like), symbol demappers, transforms, and the like. The user equipment may further include at least one processor, such as for example a processor 730 for controlling the user equipment and for accessing and executing program code stored in memory 735. Furthermore, the user equipment may include video cut application 799, which may be stored in a computer- readable medium, such as memory, and the like and may be configured to provide one or more aspects of the mechanisms and processes described herein including process 500.

[0053] FIG. 8 depicts an example implementation of a server 800 including a video cut generator 800. The server 800 may include a network interface 840 for accessing the internet, other servers, and/or base station/wireless access point 110. The server 800 may further includes a processor 826 for controlling the server and for accessing and executing program code stored in memory 825. Furthermore, the server 800 may include a search module 198B for searching, a cut model 198C, and a concatenator 198D for providing one or more aspects of video cut generation as described herein (including for example process 600). [0054] The subject matter described herein may be embodied in systems, apparatus, methods, and/or articles depending on the desired configuration. For example, the user equipment (or one or more components therein) and/or the processes described herein can be implemented using one or more of the following: a processor executing program code, an application-specific integrated circuit (ASIC), a digital signal processor (DSP), an embedded processor, a field programmable gate array (FPGA), and/or combinations thereof. These various implementations may include implementation in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device. These computer programs (also known as programs, software, software applications, applications, components, program code, or code) include machine instructions for a programmable processor, and may be implemented in a high-level procedural and/or object-oriented programming language, and/or in assembly/machine language. As used herein, the term "machine-readable medium" refers to any computer program product, computer-readable medium, apparatus and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions. Similarly, systems are also described herein that may include a processor and a memory coupled to the processor. The memory may include one or more programs that cause the processor to perform one or more of the operations described herein. [0055] Although a few variations have been described in detail above, other modifications or additions are possible. In particular, further features and/or variations may be provided in addition to those set forth herein. For example, the implementations described above may be directed to various combinations and subcombinations of the disclosed features and/or combinations and subcombinations of several further features disclosed above. In addition, the logic flow depicted in the accompanying figures and/or described herein does not require the particular order shown, or sequential order, to achieve desirable results. In various example embodiments, the methods (or processes) can be accomplished on user equipment/mobile device side or on the server side or in any shared way between server and user equipment/mobile device with actions being performed on both sides. The phrases "based on" and "based on at least" are used interchangeably herein. Other embodiments may be within the scope of the following claims.

Claims

WHAT IS CLAIMED:

1 . A method comprising causing at least in part:

processing one or more search parameters to search metadata associated with one or more videos, wherein the metadata comprises information from one or more sources and context information, or a combination thereof, derived from the metadata; and

processing one or more model parameters to form a composite video based at least in part on the processing of the one or more search parameters.

2. A method as in claim 1 , wherein the metadata includes one or more of information obtained from a website hosting the one or more videos, a first information from a first user that generated the one or more videos, and a second information from a second user other than the user that generated the one or more videos, or a combination thereof.

3. A method as in any of the preceding claims, wherein the metadata includes information derived from the metadata associated with the one or more videos.

4. A method as in any of the preceding claims, wherein the metadata includes context information derived from location information associated with the one or more videos.

5. A method as in any of the preceding claims, wherein the metadata includes context information derived from information about a user associated with the one or more videos, wherein the information about the user is obtained from a second website other than a first website hosting the one or more videos.

6. A method as in any of the preceding claims, wherein the metadata includes one or more of a multimedia metadata and a textual annotation provided by a user.

7. A method as in any of the preceding claims further comprising:

receiving the composite video after the search of the metadata, wherein the search is performed by comparing the one or more search parameters with one or more topics characterizing the metadata.

8. A method as in any of the preceding claims further comprising:

identifying the one or more candidate videos based on at least a match of the one or more search parameters and one or more topics characterizing the metadata.

9. A method as in any of the preceding claims further comprising

concatenating one or more candidate videos identified by the search.

10. A method as in any of the preceding claims further comprising:

generating a user interface to enable modifying the one or more model parameters, wherein the modification causes another composite video to be received.

1 1 . A method as in any of the preceding claims further comprising:

providing the one or more search parameters to enable the search.

12. A method as in any of the preceding claims further comprising: providing the one or more model parameters to enable formation of the composite video.

13. An apparatus comprising means for performing a method of any of claims 1 -12.

14. The apparatus of claim 13, wherein the apparatus comprises a user equipment.

15. A computer-readable storage medium carrying one or more sequences of one or more instructions which, when executed by one or more processors, cause an apparatus to perform at least a method of any of claims 1 -12.

16. A method comprising:

receiving one or more search parameters to search metadata associated with one or more videos, wherein the metadata comprises information from one or more sources and context information, or a combination thereof, derived from the metadata;

receiving one or more model parameters to form a composite video based at least in part on the received one or more search parameters;

concatenating, based on at least the one or more model parameters, one or more candidate videos to form the composite video; and

providing the composite video.

17. A method as in claim 16 further comprising: searching, based one or more search parameters received from a user equipment, the metadata associated with one or more videos.

18. A method as in any of claims 16 and 17 further comprising:

receiving from the user equipment at least one other model parameter to cause at least another composite video to be formed.

19. A method as in any of claims 16-18, wherein the metadata includes one or more of information obtained from a website hosting the one or more videos, information from a user that generated the one or more videos, and information from a second user other than the user that generated the one or more videos, or a combination thereof.

20. A method as in any of claims 16-19, wherein the metadata includes information derived from the metadata associated with the one or more videos.

21 . A method as in any of claims 16-20, wherein the metadata includes context information derived from location information associated with the one or more videos.

22. A method as in any of claims 16-21 , wherein the metadata includes context information derived from information about a user associated with the one or more videos, wherein the information about the user is obtained from a second website other than a first website hosting the one or more videos.

23. A method as in any of claims 16-22, wherein the metadata includes one or more of a multimedia metadata and a textual annotation provided by a user.

24. A method as in any of claims 16-23 further comprising:

identifying at least one of the one or more candidate videos by searching topics determined from the metadata associated with the one or more videos.

25. A method as in any of claims 16-24 further comprising:

searching by at least comparing the one or more search parameters with one or more topics characterizing the metadata.

26. An apparatus comprising means for performing a method of any of claims 16-

25.

27. The apparatus of claim 26, wherein the apparatus comprises a server coupled to the Internet.

28. A computer-readable storage medium carrying one or more sequences of one or more instructions which, when executed by one or more processors, cause an apparatus to perform at least a method of any of claims 16-25.