CN111666449B

CN111666449B - Video retrieval method, apparatus, electronic device, and computer-readable medium

Info

Publication number: CN111666449B
Application number: CN202010579635.7A
Authority: CN
Inventors: 孙婉轩; 赵嘉伟; 王长虎
Original assignee: Douyin Vision Co Ltd
Current assignee: Douyin Vision Co Ltd
Priority date: 2020-06-23
Filing date: 2020-06-23
Publication date: 2023-04-25
Anticipated expiration: 2040-06-23
Also published as: CN111666449A; WO2021258972A1

Abstract

Embodiments of the present disclosure disclose video retrieval methods, apparatus, electronic devices, and computer-readable media. One embodiment of the method comprises the following steps: searching in a video library based on the target video set to obtain a search result; for the video in the search result, generating an associated video corresponding to the video, and obtaining an associated video set corresponding to the search result; searching in a video library based on the associated video set, and determining whether videos meeting preset conditions exist. This embodiment achieves an improvement in accuracy of the search result.

Description

Video retrieval method, apparatus, electronic device, and computer-readable medium

Technical Field

Embodiments of the present disclosure relate to the field of computer technology, and in particular, to a video retrieval method, apparatus, electronic device, and computer readable medium.

Background

Video retrieval is common to various scenes such as video searching, video deduplication, infringement video off-shelf, and the like. For some video after editing (e.g. editing, adding special effects), the general search method easily omits the video, so that the search result is inaccurate.

Disclosure of Invention

The disclosure is in part intended to introduce concepts in a simplified form that are further described below in the detailed description. The disclosure is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.

Some embodiments of the present disclosure propose video retrieval methods, apparatuses, electronic devices, and computer-readable media to solve the technical problems mentioned in the background section above.

In a first aspect, some embodiments of the present disclosure provide a video retrieval method, including: searching in a video library based on the target video set to obtain a search result; for the video in the search result, generating an associated video corresponding to the video, and obtaining an associated video set corresponding to the search result; searching in a video library based on the associated video set, and determining whether videos meeting preset conditions exist.

In a second aspect, some embodiments of the present disclosure provide a video retrieval apparatus comprising: the first retrieval unit is configured to retrieve in the video library based on the target video set to obtain a retrieval result; the generation unit is configured to generate associated videos corresponding to the videos for the videos in the search result, and obtain an associated video set corresponding to the search result; and the second searching unit is configured to search in the video library based on the associated video set and determine whether videos meeting preset conditions exist.

In a third aspect, some embodiments of the present disclosure provide an electronic device comprising: one or more processors; and a storage device having one or more programs stored thereon, which when executed by the one or more processors, cause the one or more processors to implement the method of any of the above.

In a fourth aspect, some embodiments of the present disclosure provide a computer readable medium having a computer program stored thereon, wherein the program when executed by a processor implements any of the methods described above.

One of the above embodiments of the present disclosure has the following advantageous effects: and generating a corresponding associated video for the search result, and further searching based on the associated video to improve the searching accuracy. Wherein, the video obtained after various editing (such as editing and adding special effects) can be simulated by the associated video. Therefore, the video is searched based on the associated video, and the edited video is more easily searched, so that the accuracy of a search result is improved.

Drawings

The above and other features, advantages, and aspects of embodiments of the present disclosure will become more apparent by reference to the following detailed description when taken in conjunction with the accompanying drawings. The same or similar reference numbers will be used throughout the drawings to refer to the same or like elements. It should be understood that the figures are schematic and that elements and components are not necessarily drawn to scale.

FIG. 1 is a schematic illustration of one application scenario of a video retrieval method according to some embodiments of the present disclosure;

FIG. 2 is a flow chart of some embodiments of a video retrieval method according to the present disclosure;

FIG. 3 is a flow chart of further embodiments of a video retrieval method according to the present disclosure;

FIG. 4 is a schematic diagram of another application scenario of a video retrieval method according to some embodiments of the present disclosure;

FIG. 5 is a schematic structural diagram of some embodiments of a video retrieval device according to the present disclosure;

fig. 6 is a schematic structural diagram of an electronic device suitable for use in implementing some embodiments of the present disclosure.

Detailed Description

Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete. It should be understood that the drawings and embodiments of the present disclosure are for illustration purposes only and are not intended to limit the scope of the present disclosure.

It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings. Embodiments of the present disclosure and features of embodiments may be combined with each other without conflict.

It should be noted that the terms "first," "second," and the like in this disclosure are merely used to distinguish between different devices, modules, or units and are not used to define an order or interdependence of functions performed by the devices, modules, or units.

It should be noted that references to "one", "a plurality" and "a plurality" in this disclosure are intended to be illustrative rather than limiting, and those of ordinary skill in the art will appreciate that "one or more" is intended to be understood as "one or more" unless the context clearly indicates otherwise.

The names of messages or information interacted between the various devices in the embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

Fig. 1 is a schematic diagram 100 of one application scenario of a video retrieval method according to some embodiments of the present disclosure.

The video retrieval method provided by some embodiments of the present disclosure may be performed by a terminal device or may be performed by a server. The terminal device and the server may be hardware or software. When hardware, it may be a variety of electronic devices including, but not limited to, smartphones, tablet computers, electronic book readers, vehicle terminals, and the like. When it is software, it can be installed in the above-listed electronic device. It may be implemented as a plurality of software or software modules, for example, for providing distributed services, or as a single software or software module. The present invention is not particularly limited herein.

In this scenario, it is necessary to retrieve infringement videos in a video library. As shown in fig. 1, the execution subject of the video retrieval method may be a server 101. The server 101 may first perform a search in the video library 103 based on the target video set 102, resulting in a search result 104. As an example, the videos in the target video set 102 may be trending videos over a period of time (e.g., over the past three hours). In practice, a trending video may be one where interaction data (e.g., forwarding volume, praise volume, comment volume, etc.) is greater than a preset threshold. Here, the trending videos are retrieved as the target video set because the hotter videos are more likely to be infringing. In this way, it is easier to retrieve infringement videos. On this basis, the server 101 may generate an associated video set 105 corresponding to the search result 104. As an example, the video in the search results 104 may be scaled, cropped, framed, de-framed, tri-folded, etc., to obtain an associated video. The server 101 may then retrieve in the video library 103 based on the associated video set 105, determining whether there is a video satisfying the preset condition. As an example, it may be determined whether there is a video that has a post-publication time later than the video in the target video set 102. Alternatively, if present, these videos may be determined as infringement videos, and the infringement videos may be subjected to processing such as deletion.

With continued reference to fig. 2, a flow 200 of some embodiments of a video retrieval method according to the present disclosure is shown. The video retrieval method comprises the following steps:

and step 201, searching in a video library based on the target video set to obtain a search result.

In some embodiments, the execution subject of the video retrieval method may retrieve in the video library based on the target video set, thereby obtaining a retrieval result. Specifically, at least one video in the target video set can be matched in a video library, so as to obtain a search video corresponding to each video in the at least one video. On the basis, the search videos corresponding to the videos in at least one video are summarized to obtain search results. Wherein the videos in the target video set can be obtained in various ways. As an example, the determination may be performed in a specified manner, or may be obtained by screening under certain conditions. The video library can be a collection comprising a large number of videos, and can be specified according to actual needs or screened according to certain conditions.

In some embodiments, video matching or retrieval may be performed in various ways. As an example, video matching or retrieval may be performed by calculating the similarity of key frames. As yet another example, video matching or retrieval may also be performed by calculating the distance between features of different videos.

In some alternative implementations of some embodiments, prior to step 201, the method further includes: and selecting videos with preset indexes larger than a preset threshold value from a video library as a target video set based on the interaction data of the videos. In practice, the interaction data of the video includes, but is not limited to: forwarding volume, praise volume, comment volume, play volume, etc. The preset index may be one or more of the interaction data. In these implementations, the target set of videos is determined based on the interaction data because the higher the interaction data, the hotter these videos can be considered. And the higher the likelihood that the hot video is edited. In a scenario similar to infringement video retrieval, it is easier to retrieve the infringement video.

Step 202, for the video in the search result, generating an associated video corresponding to the video, and obtaining an associated video set corresponding to the search result.

In some embodiments, for a certain video in the search result, the executing entity may generate the associated video corresponding to the video through various methods (such as data augmentation). Similarly, for some or all of the videos in the search result, a plurality of associated videos corresponding to the videos may be generated. Further, the plurality of related videos may be set as related videos corresponding to the search result. As an example, the corresponding associated video may be generated by performing processing such as cropping, scaling, adding special effects, and the like on the video.

In some optional implementations of some embodiments, for the video in the search result, generating an associated video corresponding to the video, to obtain an associated video set corresponding to the search result, including: selecting a first preset number of videos from the search result; and generating associated videos corresponding to the videos in the first preset number of videos to obtain an associated video set corresponding to the search result. In these implementations, the first preset number may be any number. The first number of videos may be selected from the search results in various ways according to actual needs. For example, the first preset number of videos may be selected according to a sequence from large to small of interaction data (e.g., praise amount, forwarding amount, play amount, etc.) of the videos. As another example, the first preset data may be selected randomly. In the implementation modes, the workload of generating the associated videos can be reduced and the running speed can be improved by selecting the preset number of videos.

And 203, searching in a video library based on the associated video set, and determining whether videos meeting preset conditions exist.

In some embodiments, the executing entity may search the video library based on the associated video set to determine whether a video satisfying a preset condition exists. According to actual needs, one or more videos in the associated video set may be retrieved in a video library. In practice, the preset conditions may be different according to the actual needs. As an example, for a scenario in which infringement videos are retrieved, it may be determined whether there is a video that has been published later in time than the videos in the target video set. This is because the infringement video is a video edited on the basis of the original video (video in the target video set), and thus its distribution time is generally later than the original video.

According to the method provided by some embodiments of the present disclosure, for the search result, a corresponding associated video is generated, and further, based on the associated video search, the search accuracy is improved. Wherein, the video obtained after various editing (such as editing and adding special effects) can be simulated by the associated video. Therefore, the video is searched based on the associated video, and the edited video is more easily searched, so that the accuracy of a search result is improved.

With further reference to fig. 3, a flow 300 of further embodiments of a video retrieval method is shown. The video retrieval method flow 300 includes the steps of:

step 301, searching in a video library based on the target video set to obtain a search result.

In some embodiments, the specific implementation of step 301 and the technical effects thereof may refer to step 201 in those embodiments corresponding to fig. 2, which are not described herein.

Step 302, extracting visual features from the search result to obtain a visual feature set.

In some embodiments, the execution subject of the video retrieval method may perform visual feature extraction on the retrieval result, thereby obtaining a set of visual features. According to actual needs, visual feature extraction can be performed on part or all of videos in the search result, and a visual feature set is obtained. As an example, ORB features, SIFT features, and the like of a video may be extracted as visual features.

Step 303, clustering the set of visual features to obtain at least one cluster of visual features.

In some embodiments, the executing entity may cluster the plurality of visual features in the set of visual features obtained in step 302, thereby obtaining at least one cluster of visual features. Wherein, the plurality of visual features can be clustered through a clustering algorithm such as a K-means algorithm, a mean shift algorithm and the like. Various clustering algorithms may group similar ones of the plurality of visual features into the same cluster, resulting in at least one cluster of visual features.

At step 304, at least one video cluster is obtained based on the at least one cluster of visual features.

In some embodiments, since the visual features are extracted from the video, the search results may be divided into at least one video cluster according to the correspondence of the visual features to the video. That is, videos corresponding to the respective visual features in the same visual feature cluster are also divided into the same video cluster.

Step 305, for a video cluster in the at least one video cluster, determining a hotscore for the video cluster.

In some embodiments, for each of the at least one video cluster obtained in step 304, a hotscore for the video cluster may be determined. As an example, the sum of the hotness scores of the individual videos in the video cluster may be determined as the hotness score of the video cluster. Wherein the hotness score for each video may be derived from the interaction data (e.g., play volume, etc.) for that video. Specifically, as an example, the play amount may be multiplied by a preset coefficient to obtain a hotness score of the video. As yet another example, an average of the hotness scores of the individual videos in the video cluster may also be determined as the hotness score of the video cluster.

And step 306, selecting a second preset number of video clusters from at least one video cluster according to the sequence of the hotness scores from high to low.

In some embodiments, the executing body may select a second preset number of video clusters from the at least one video cluster according to the order of the hotness score from the high to the low.

Step 307, for the video in the selected video cluster, generating an associated video corresponding to the video, and obtaining an associated video set corresponding to the search result.

In some embodiments, the step 202 in the embodiment corresponding to fig. 2 may be referred to for details of the implementation of the associated video set corresponding to the search result and the technical effects thereof, which are not described herein.

Step 308, searching in the video library based on the associated video set, and determining whether a video meeting the preset condition exists.

In some embodiments, the specific implementation of step 308 and the technical effects thereof may refer to step 203 in the corresponding embodiment of fig. 2, which is not described herein.

In step 309, in response to determining that there are videos that satisfy the preset condition, adding the videos that satisfy the preset condition to the target video set.

In some embodiments, in response to determining that there are videos that satisfy the preset condition, the executing entity may add the videos that satisfy the preset condition to the target video set. Wherein, can set for suitable preset condition according to actual need. As an example, in a scenario where an infringement video is retrieved, the preset condition may be: the release time is later than the videos in the target video set.

As can be seen from fig. 3, at least one video cluster is obtained by clustering the visual features, as compared to the description of some embodiments corresponding to fig. 2. On the basis, the selection is performed according to the hotness score. Therefore, the screening of videos in the search result is realized, and the number of associated videos is reduced. And further, in the process of searching based on the associated video, the searching speed is improved. In addition, the continuous updating of the target video set is realized by adding the video meeting the preset condition into the target video set. Therefore, the subsequent retrieval based on the target video set is facilitated, and a foundation is provided for improving the accuracy of the subsequent retrieval.

With continued reference to fig. 4, fig. 4 is a schematic diagram 400 of another application scenario of a video retrieval method according to some embodiments of the present disclosure.

In the present application scenario, the execution subject of the video retrieval method may be the server 401. The server 401 may first retrieve in the video library 403 based on the target video set 402, resulting in a retrieval result 404. On this basis, visual feature extraction can be performed on the video in the search result 404, so as to obtain a visual feature set 405. Then, the visual feature sets 405 are clustered to obtain n visual feature clusters 406. The search result 404 is also divided into n video clusters 407 according to n visual feature clusters 406. A hotness score is calculated 408 for each video cluster separately. As an example, a weighted sum of the play volume and the search volume may be determined as the hotness score 408. M video clusters 409 are selected from the n video clusters 407 according to the order of the hotness score 408 from high to low. Typically, m is less than n. Then, for the videos in the m video clusters 409, corresponding associated videos are generated, and an associated video set 410 is obtained. On this basis, it is determined whether there is a video satisfying the preset condition based on the retrieval of the associated video set 410 in the video library 403. If so, videos meeting the preset conditions may be added to the target video collection 402.

With further reference to fig. 5, as an implementation of the method shown in the above figures, the present disclosure provides some embodiments of a video retrieval apparatus, which apparatus embodiments correspond to those method embodiments shown in fig. 2, and which apparatus is particularly applicable in a variety of electronic devices.

As shown in fig. 5, the video retrieval apparatus 500 of some embodiments includes: a first retrieving unit 501, a generating unit 502 and a second retrieving unit 503. Wherein, the first searching unit 501 is configured to search in the video library based on the target video set to obtain a search result. The generating unit 502 is configured to generate, for the video in the search result, an associated video corresponding to the video, and obtain an associated video set corresponding to the search result. The second retrieving unit 503 is configured to perform retrieval in the video library based on the associated video set, and determine whether there is a video satisfying a preset condition.

In some embodiments, the first search unit 501, the generating unit 502, and the second search unit 503 in the video search apparatus 500 are specifically implemented and technical effects thereof, and reference may be made to those embodiments corresponding to fig. 2, which are not described herein.

In an alternative implementation of some embodiments, the generating unit 502 may be further configured to select a first preset number of videos from the search result; and generating associated videos corresponding to the videos in the first preset number of videos to obtain an associated video set corresponding to the search result.

In alternative implementations of some embodiments, the generating unit 502 may be further configured to: clustering the search results to obtain at least one video cluster; selecting a second preset number of video clusters from at least one video cluster; and generating associated videos corresponding to the videos in the selected video clusters to obtain associated video sets corresponding to the search results.

In alternative implementations of some embodiments, the generating unit 502 may be further configured to: extracting visual features of the search result to obtain a visual feature set; clustering the visual feature sets to obtain at least one visual feature cluster; at least one video cluster is derived based on the at least one cluster of visual features.

In alternative implementations of some embodiments, the generating unit 502 may be further configured to: for a video cluster in the at least one video cluster, determining a hotscore for the video cluster; and selecting a second preset number of video clusters from at least one video cluster according to the sequence of the hotness scores from high to low.

In alternative implementations of some embodiments, the apparatus 500 may further include: and selecting videos with preset indexes larger than a preset threshold value from a video library as a target video set based on the interaction data of the videos.

In alternative implementations of some embodiments, the apparatus 500 may further include: and in response to determining that the videos meeting the preset conditions exist, adding the videos meeting the preset conditions into the target video set.

In some embodiments, for the search result, a corresponding associated video is generated, so that the search accuracy is improved based on the associated video search. Wherein, the video obtained after various editing (such as editing and adding special effects) can be simulated by the associated video. Therefore, the video is searched based on the associated video, and the edited video is more easily searched, so that the accuracy of a search result is improved.

Referring now to fig. 6, a schematic diagram of an electronic device (e.g., server in fig. 1) 600 suitable for use in implementing some embodiments of the present disclosure is shown. The electronic device shown in fig. 6 is merely an example and should not impose any limitations on the functionality and scope of use of embodiments of the present disclosure.

As shown in fig. 6, the electronic device 600 may include a processing means (e.g., a central processing unit, a graphics processor, etc.) 601, which may perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 602 or a program loaded from a storage means 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the electronic apparatus 600 are also stored. The processing device 601, the ROM 602, and the RAM 603 are connected to each other through a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.

In general, the following devices may be connected to the I/O interface 605: input devices 606 including, for example, a touch screen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, and the like; an output device 607 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 608 including, for example, magnetic tape, hard disk, etc.; and a communication device 609. The communication means 609 may allow the electronic device 600 to communicate with other devices wirelessly or by wire to exchange data. While fig. 6 shows an electronic device 600 having various means, it is to be understood that not all of the illustrated means are required to be implemented or provided. More or fewer devices may be implemented or provided instead. Each block shown in fig. 6 may represent one device or a plurality of devices as needed.

In particular, according to some embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flow chart. In such embodiments, the computer program may be downloaded and installed from a network via communications device 609, or from storage device 608, or from ROM 602. The above-described functions defined in the methods of some embodiments of the present disclosure are performed when the computer program is executed by the processing device 601.

It should be noted that the computer readable medium according to some embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In some embodiments of the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, the computer-readable signal medium may comprise a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.

In some implementations, the clients, servers may communicate using any currently known or future developed network protocol, such as HTTP (HyperText Transfer Protocol ), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the internet (e.g., the internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed networks.

The computer readable medium may be contained in the electronic device; or may exist alone without being incorporated into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: searching in a video library based on the target video set to obtain a search result; for the video in the search result, generating an associated video corresponding to the video, and obtaining an associated video set corresponding to the search result; searching in a video library based on the associated video set, and determining whether videos meeting preset conditions exist.

Computer program code for carrying out operations for some embodiments of the present disclosure may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units described in some embodiments of the present disclosure may be implemented by means of software, or may be implemented by means of hardware. The described units may also be provided in a processor, for example, described as: a processor includes a first retrieval unit, a generation unit, and a second retrieval unit. The names of these units do not in some way limit the unit itself, for example, the first search unit may also be described as "a unit searching in a video library for a target video set".

The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a system on a chip (SOC), a Complex Programmable Logic Device (CPLD), and the like.

According to one or more embodiments of the present disclosure, there is provided a video retrieval method including: searching in a video library based on the target video set to obtain a search result; for the video in the search result, generating an associated video corresponding to the video, and obtaining an associated video set corresponding to the search result; searching in a video library based on the associated video set, and determining whether videos meeting preset conditions exist.

According to one or more embodiments of the present disclosure, for a video in a search result, generating an associated video corresponding to the video, to obtain an associated video set corresponding to the search result, including: selecting a first preset number of videos from the search result; and generating associated videos corresponding to the videos in the first preset number of videos to obtain an associated video set corresponding to the search result.

According to one or more embodiments of the present disclosure, for a video in a search result, generating an associated video corresponding to the video, to obtain an associated video set corresponding to the search result, including: clustering the search results to obtain at least one video cluster; selecting a second preset number of video clusters from at least one video cluster; and generating associated videos corresponding to the videos in the selected video clusters to obtain associated video sets corresponding to the search results.

According to one or more embodiments of the present disclosure, clustering search results to obtain at least one video cluster includes: extracting visual features of the search result to obtain a visual feature set; clustering the visual feature sets to obtain at least one visual feature cluster; at least one video cluster is derived based on the at least one cluster of visual features.

According to one or more embodiments of the present disclosure, selecting a second preset number of video clusters from at least one video cluster includes: for a video cluster in the at least one video cluster, determining a hotscore for the video cluster; and selecting a second preset number of video clusters from at least one video cluster according to the sequence of the hotness scores from high to low.

In accordance with one or more embodiments of the present disclosure, before retrieving in the video library based on the target video set, the method further comprises: and selecting videos with preset indexes larger than a preset threshold value from a video library as a target video set based on the interaction data of the videos.

According to one or more embodiments of the present disclosure, the method further comprises: and in response to determining that the videos meeting the preset conditions exist, adding the videos meeting the preset conditions into the target video set.

According to one or more embodiments of the present disclosure, there is provided a video retrieval apparatus including: the first retrieval unit is configured to retrieve in the video library based on the target video set to obtain a retrieval result; the generation unit is configured to generate associated videos corresponding to the videos for the videos in the search result, and obtain an associated video set corresponding to the search result; and the second searching unit is configured to search in the video library based on the associated video set and determine whether videos meeting preset conditions exist.

According to one or more embodiments of the present disclosure, the generating unit may be further configured to select a first preset number of videos from the search result; and generating associated videos corresponding to the videos in the first preset number of videos to obtain an associated video set corresponding to the search result.

According to one or more embodiments of the present disclosure, the generating unit may be further configured to: clustering the search results to obtain at least one video cluster; selecting a second preset number of video clusters from at least one video cluster; and generating associated videos corresponding to the videos in the selected video clusters to obtain associated video sets corresponding to the search results.

According to one or more embodiments of the present disclosure, the generating unit may be further configured to: extracting visual features of the search result to obtain a visual feature set; clustering the visual feature sets to obtain at least one visual feature cluster; at least one video cluster is derived based on the at least one cluster of visual features.

According to one or more embodiments of the present disclosure, the generating unit may be further configured to: for a video cluster in the at least one video cluster, determining a hotscore for the video cluster; and selecting a second preset number of video clusters from at least one video cluster according to the sequence of the hotness scores from high to low.

In accordance with one or more embodiments of the present disclosure, the apparatus may further include: and selecting videos with preset indexes larger than a preset threshold value from a video library as a target video set based on the interaction data of the videos.

In accordance with one or more embodiments of the present disclosure, the apparatus may further include: and in response to determining that the videos meeting the preset conditions exist, adding the videos meeting the preset conditions into the target video set.

According to one or more embodiments of the present disclosure, there is provided an electronic device including: one or more processors; and a storage device having one or more programs stored thereon, which when executed by the one or more processors, cause the one or more processors to implement the method as described in any of the embodiments above.

According to one or more embodiments of the present disclosure, there is provided a computer readable medium having stored thereon a computer program, wherein the program, when executed by a processor, implements a method as described in any of the embodiments above.

The foregoing description is only of the preferred embodiments of the present disclosure and description of the principles of the technology being employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above technical features, but encompasses other technical features formed by any combination of the above technical features or their equivalents without departing from the spirit of the invention. Such as the above-described features, are mutually substituted with (but not limited to) the features having similar functions disclosed in the embodiments of the present disclosure.

Claims

1. A video retrieval method comprising:

searching in a video library based on the target video set to obtain a search result;

generating associated videos corresponding to the videos in the search results to obtain associated video sets corresponding to the search results; the method specifically comprises the following steps:

extracting visual features from the search result to obtain a visual feature set;

clustering the visual feature sets to obtain at least one visual feature cluster;

obtaining the at least one video cluster based on the at least one visual feature cluster;

determining a hotness score for a video cluster of the at least one video cluster;

selecting a second preset number of video clusters from the at least one video cluster according to the sequence of the hotness scores from high to low;

generating associated videos corresponding to the videos in the selected video clusters to obtain associated video sets corresponding to the search results; the associated video is a video obtained by editing the target video;

and searching in the video library based on the associated video set, and determining whether videos meeting preset conditions exist.

2. The method of claim 1, wherein the generating, for the video in the search result, the associated video corresponding to the video, to obtain the associated video set corresponding to the search result, includes:

selecting a first preset number of videos from the search result;

and generating associated videos corresponding to the videos in the first preset number of videos to obtain an associated video set corresponding to the search result.

3. The method of claim 1, wherein prior to retrieving in a video library based on the target video collection, the method further comprises:

and selecting videos with preset indexes larger than a preset threshold value from the video library as the target video set based on the interaction data of the videos.

4. The method of any of claims 1-2, wherein the method further comprises:

and in response to determining that the videos meeting the preset conditions exist, adding the videos meeting the preset conditions into the target video set.

5. A video retrieval apparatus comprising:

the first retrieval unit is configured to retrieve in the video library based on the target video set to obtain a retrieval result;

the generation unit is configured to generate associated videos corresponding to the videos in the search results to obtain an associated video set corresponding to the search results; the method specifically comprises the following steps:

and the second searching unit is configured to search in the video library based on the associated video set and determine whether videos meeting preset conditions exist.

6. An electronic device, comprising:

one or more processors;

a storage device having one or more programs stored thereon,

when executed by the one or more processors, causes the one or more processors to implement the method of any of claims 1-4.

7. A computer readable medium having stored thereon a computer program, wherein the program when executed by a processor implements the method of any of claims 1-4.