Video skimming methods and systems
First Claim
1. A method of creating a skimming preview of a video, the method comprising:
- electronically receiving a plurality of video shots;
analyzing each frame in a video shot from the plurality of video shots, analyzing comprising determining a saliency of each frame of the video shot;
selecting a key frame of the video shot based on the saliency of each frame of the video shot after determining the saliency of each frame in the video shot;
extracting visual features from the key frame after selecting the key frame;
performing shot clustering of the plurality of video shots to determine concept patterns based on the visual features; and
generating a reconstruction reference tree based on the shot clustering, the reconstruction reference tree comprising video shots categorized according to each concept pattern, wherein generating the reconstruction reference tree comprises categorizing video shots within concept categories ordered according to concept importance, and ordering video shots within each concept category according to saliency.
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Accused Products
Abstract
In an embodiment, a method of creating a skimming preview of a video includes electronically receiving a plurality of video shots, analyzing each frame in a video shot from the plurality of video shots, where analyzing includes determining a saliency of each frame of the video shot. The method also includes determining a key frame of the video shot based on the saliency of each frame the video shot, extracting visual features from the key frame, performing shot clustering of the plurality of video shots to determine concept patterns based on the visual features, and generating a reconstruction reference tree based on the shot clustering. The reconstruction reference tree includes video shots categorized according to each concept pattern.
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Citations
32 Claims
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1. A method of creating a skimming preview of a video, the method comprising:
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electronically receiving a plurality of video shots; analyzing each frame in a video shot from the plurality of video shots, analyzing comprising determining a saliency of each frame of the video shot; selecting a key frame of the video shot based on the saliency of each frame of the video shot after determining the saliency of each frame in the video shot; extracting visual features from the key frame after selecting the key frame; performing shot clustering of the plurality of video shots to determine concept patterns based on the visual features; and generating a reconstruction reference tree based on the shot clustering, the reconstruction reference tree comprising video shots categorized according to each concept pattern, wherein generating the reconstruction reference tree comprises categorizing video shots within concept categories ordered according to concept importance, and ordering video shots within each concept category according to saliency. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 27, 28)
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17. A method of generating a skimming preview of a video, the method comprising:
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electronically receiving a reconstruction reference tree comprising video shots categorized within concept categories ordered according to concept importance, wherein video shots within each concept category is ordered according to saliency; determining a skimming ratio; selecting shots starting from categories of highest importance and shots of highest saliency within the categories of highest importance; and generating the skimming preview based on the selected shots. - View Dependent Claims (18, 19)
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20. A system for creating a skimming preview of a video, the system comprising:
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an I/O port electronically receiving a plurality of video shots; and a hardware circuit coupled to the I/O port, the hardware circuit comprising a saliency analyzer determining a saliency of each frame of a video shot from the plurality of video shots, a key frame selector selecting a key frame of the video shot based on the saliency of each frame in the video shot after the saliency analyzer determines the saliency of each frame in the video shot, a visual feature extractor extracting visual features from the key frame after the key frame selector selects the key frame, a shot clustering block performing shot clustering of the plurality of video shots to determine concept patterns based on the visual features, and a reconstruction reference tree generator generating a reconstruction reference tree based on the shot clustering, the reconstruction reference tree comprising video shots categorized according to each concept pattern, wherein the reconstruction reference tree generator is configured to generate the reconstruction reference tree by categorizing video shots within concept categories ordered according to concept importance, and ordering video shots within each concept category according to saliency. - View Dependent Claims (21, 22, 26, 29, 30)
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23. A non-transitory computer readable medium with an executable program stored thereon, wherein the program instructs a microprocessor to perform the following steps:
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analyzing each frame in a video shot from a plurality of video shots, analyzing comprising determining a saliency of each frame of the video shot; selecting a key frame of the video shot based on the saliency of each frame of the video shot after determining the saliency of each frame in the video shot; extracting visual features from the key frame after selecting the key frame; performing shot clustering of the plurality of video shots to determine concept patterns based on the visual features; and generating a reconstruction reference tree based on the shot clustering, the reconstruction reference tree comprising video shots categorized according to each concept pattern, wherein generating the reconstruction reference tree comprises categorizing video shots within concept categories ordered according to concept importance, and ordering video shots within each concept category according to the saliency. - View Dependent Claims (24, 25, 31, 32)
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Specification