Method and apparatus for video searches and index construction

1. A method comprising:

receiving a search request input by a user to search for a target video, the search request including multimodal search data for the target video;

obtaining a processing result, utilizing a pre-configured algorithm, based on the multimodal search data, the processing result comprising one or more semantic labels for the multimodal search data generated by the pre-configured algorithm; and

using the processing result to search a corresponding pre-constructed index, the pre-constructed index based on the processing result to obtain the target video.

2. The method of claim 1 , the multimodal search data comprising text data and the obtaining a processing result of the multimodal search data comprising: processing the text data based on a pre-configured text algorithm to obtain a semantic text label of the text data.

3. The method of claim 1 , the multimodal search data comprising image data and the obtaining a processing result of the multimodal search data comprising:

processing the image data based on a pre-configured image algorithm to obtain a semantic image label of the image data; and

processing the image data based on a pre-configured vectorization model to obtain a vectorized description of the image data.

4. The method of claim 1 , the multimodal search data comprising video data, the method further comprising:

processing the video data into video metadata and video stream data; and

segmenting the video stream data into a sequence of video frames based on a pre-configured segmenting manner.

5. The method of claim 4 , the obtaining a processing result of the multimodal search data based on the multimodal search data comprising:

processing the video metadata based on a text algorithm to obtain a semantic text label of the video metadata;

processing video frames in the sequence of video frames based on a pre-configured video algorithm to obtain semantic video labels of the video frames; and

processing the video frames based on a vectorization model to obtain vectorized descriptions of the video frames.

6. The method of claim 2 , the providing the processing result of the multimodal search data with regard to a corresponding pre-constructed index to search to obtain the target video comprising providing a semantic text label of text data with regard to a corresponding pre-constructed inverted index to search to obtain the target video.

7. The method of claim 3 , the providing the processing result of the multimodal search data with regard to a corresponding pre-constructed index to search to obtain the target video comprising:

providing the semantic image label with regard to a corresponding pre-constructed inverted index to search to obtain a first initial video;

providing the vectorized description of the image data with regard to a corresponding pre-constructed vector index to search to obtain a second initial video; and

obtaining the target video based on the first initial video and the second initial video.

8. The method of claim 5 , the providing the processing result of the multimodal search data with regard to a corresponding pre-constructed index to search to obtain the target video comprising:

providing the semantic text label of the video metadata with regard to a corresponding pre-constructed inverted index to search to obtain a third initial video;

providing the vectorized descriptions of the video frames with regard to a corresponding pre-constructed vector index to search to obtain a fourth initial video; and

obtaining the target video based on the third initial video and the fourth initial video.

9. The method of claim 7 , the providing the semantic image label with regard to obtain a first initial video comprising:

combining the semantic image label and the semantic text label of the text data to generate a combined label; and

providing the combined label with regard to the corresponding pre-constructed inverted index to search to obtain the first initial video.

10. The method of claim 8 , the providing the semantic text label of the video metadata with regard to a corresponding pre-constructed inverted index to search to obtain a third initial video comprising:

combining the semantic text label of the video metadata, the semantic text label of the text data, and the semantic video labels of the video frames to generate a combined label; and

providing the combined label with regard to the corresponding pre-constructed inverted index to search to obtain the third initial video.

11. The method of claim 1 , the index being constructed by:

obtaining video data;

processing the video data into video metadata and video stream data;

processing the video metadata based on a pre-configured text algorithm to obtain a text processing result of the video metadata;

processing the video stream data based on a pre-configured video algorithm and vectorization model, respectively, to obtain a video processing result and a vectorization processing result of the video stream data;

constructing an inverted index based on the text processing result and the video processing result; and

constructing a vector index based on the vectorization processing result.

12. An apparatus comprising:

a processor; and

a storage medium for tangibly storing thereon program logic for execution by the processor, the stored program logic comprising:

logic, executed by the processor, for receiving a search request input by a user to search for a target video, the search request including multimodal search data for the target video,

logic, executed by the processor, for obtaining a processing result, utilizing a pre-configured algorithm, based on the multimodal search data, the processing result comprising one or more semantic labels for the multimodal search data generated by the pre-configured algorithm; and

logic, executed by the processor, for using the processing result to search a corresponding pre-constructed index, the pre-constructed index based on the processing result to obtain the target video.

13. The apparatus of claim 12 , the multimodal search data comprising text data; and the logic for obtaining a processing result of the multimodal search data comprising:

logic, executed by the processor, for processing the text data based on a pre-configured text algorithm to obtain a semantic text label of the text data.

14. The apparatus of claim 12 , the multimodal search data image data;

and the logic for obtaining a processing result of the multimodal search data comprising:

logic, executed by the processor, for processing the image data based on a pre-configured image algorithm to obtain a semantic image label of the image data, and

logic, executed by the processor, for processing the image data based on a pre-configured vectorization model to obtain a vectorized description of the image data.

15. The apparatus of claim 12 , the multimodal search data video data; and

the logic for obtaining a processing result of the multimodal search data comprising:

logic, executed by the processor, for processing the video data into video metadata and video stream data, and

logic, executed by the processor, for segmenting the video stream data into a sequence of video frames based on a pre-configured segmenting manner.

16. The apparatus of claim 15 , the logic for obtaining a processing result of the multimodal search data comprising:

logic, executed by the processor, for processing the video metadata based on a text algorithm to obtain a semantic text label of the video metadata,

logic, executed by the processor, for processing video frames in the sequence of video frames based on a pre-configured video algorithm to obtain semantic video labels of the video frames, and

logic, executed by the processor, for processing the video frames based on a vectorization model to obtain vectorized descriptions of the video frames.

17. The apparatus of claim 12 , the logic for providing the processing result of the multimodal search data with regard to a corresponding pre-constructed index to search to obtain the target video comprising: providing a semantic text label of text data with regard to a corresponding pre-constructed inverted index to search to obtain the target video.

18. A non-transitory computer-readable storage medium for tangibly storing computer program instructions capable of being executed by a computer processor, the computer program instructions defining the steps of:

receiving a search request input by a user to search for a target video, the search request including multimodal search data for the target video;

obtaining a processing result, utilizing a pre-configured algorithm, based on the multimodal search data the processing result comprising one or more semantic labels for the multimodal search data generated by the pre-configured algorithm; and

using the processing result to search a corresponding pre-constructed index, the pre-constructed index based on the processing result to obtain the target video.

19. The computer-readable storage medium of claim 17 , the multimodal search data comprising text data and the obtaining a processing result of the multimodal search data comprising: processing the text data based on a pre- configured text algorithm to obtain a semantic text label of the text data.

20. The computer-readable storage medium of claim 17 , the multimodal search data comprising image data and the obtaining a processing result of the multimodal search data comprising:

processing the image data based on a pre-configured image algorithm to obtain a semantic image label of the image data; and

processing the image data based on a pre-configured vectorization model to obtain a vectorized description of the image data.

21. The computer-readable storage medium of claim 17 , the multimodal search data comprising video data, the method further comprising:

processing the video data into video metadata and video stream data; and

segmenting the video stream data into a sequence of video frames based on a pre-configured segmenting manner.