Generating video summary

A system comprising:

• one or more processors;
• a memory coupled to the one or more processors;
• and
• a set of computer program instructions stored in the memory and executed by the one or more processors to implement a method comprising:
• receiving a viewer request for playing a video summary of a video, wherein the viewer request includes a length of the video summary;
• and
• in response to receiving the viewer request:
• obtaining the audience reviews on the video;
• extracting images from the audience reviews, the images being derived from the video;
• extracting image features of the images to generate image feature vectors, each of the image feature vectors corresponding to a respective one of the images;
• grouping the image feature vectors into clusters, the clusters being ranked based on their sizes and each having respective center point image feature vectors;
• designating one or more images corresponding to respective center point image feature vectors of one or more top-ranked clusters of the clusters as the one or more representative images;
• determining weights of importance of the one or more representative images based on the sizes of the one or more top-ranked clusters;
• extracting textual messages from the audience reviews;
• extracting text features of the textual messages to generate text feature vectors, each of the text feature vectors corresponding to a respective one of the textual messages;
• grouping the text feature vectors into clusters each having respective center point text feature vectors that represent different topics, the topics each having respective weights of interest measured by sizes of respective clusters of the text feature vectors;
• associating each of the one or more images with one of the topics to which the representative image is most relevant;
• adjusting the weights of importance of the one or more representative images by using the weights of interest of respective associated topics;
• identifying candidate frames of the video that are similar to the one or more representative images, wherein the candidate frames are ranked in order of their confidence levels of similarity to the one or more representative images and weights of importance of the one or more representative images;
• selecting the set of frames based on the ranked candidate frames;
• generating the video summary of the viewer-requested length comprising the set of frames;
• and
• playing a video stream of the video summary.

A computer program product, wherein the computer program product comprises a computer readable storage medium having program instructions embodied therewith, wherein the program instructions are executable by one or more processors to implement a method comprising:

• receiving a viewer request for playing a video summary of a video, wherein the viewer request includes a length of the video summary;
• and
• in response to receiving the viewer request:
• obtaining, by one or more processing units, the audience reviews on the video;
• extracting, by one or more processing units, images from the audience reviews, the images being derived from the video;
• extracting, by one or more processing units, image features of the images to generate image feature vectors, each of the image feature vectors corresponding to a respective one of the images;
• grouping, by one or more processing units, the image feature vectors into clusters, the clusters being ranked based on their sizes and each having respective center point image feature vectors;
• designating, by one or more processing units, one or more images corresponding to respective center point image feature vectors of one or more top-ranked clusters of the clusters as the one or more representative images;
• determining, by one or more processing units, weights of importance of the one or more representative images based on the sizes of the one or more top-ranked clusters;
• extracting, by one or more processing units, textual messages from the audience reviews;
• extracting, by one or more processing units, text features of the textual messages to generate text feature vectors, each of the text feature vectors corresponding to a respective one of the textual messages;
• grouping, by one or more processing units, the text feature vectors into clusters each having respective center point text feature vectors that represent different topics, the topics each having respective weights of interest measured by sizes of respective clusters of the text feature vectors;
• associating, by one or more processing units, each of the one or more images with one of the topics to which the representative image is most relevant;
• adjusting, by one or more processing units, the weights of importance of the one or more representative images by using the weights of interest of respective associated topics;
• identifying, by one or more processing units, candidate frames of the video that are similar to the one or more representative images, wherein the candidate frames are ranked in order of their confidence levels of similarity to the one or more representative images and weights of importance of the one or more representative images;
• selecting, by one or more processing units, the set of frames based on the ranked candidate frames;
• generating, by one or more processing units, the video summary of the viewer-requested length comprising the set of frames;
• and
• playing a video stream of the video summary.