Method for reordering image or video search
A video search and reordering technology, which is applied in the field of image or video search and reordering, can solve the problems of low retrieval accuracy, inability to meet needs, and inaccurate ranking models, etc.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Publication Date
- 2012-10-24
Smart Images
Figure 1 Figure 2 Figure 3
Abstract
Description
technical field
[0001] The invention relates to the field of multimedia information retrieval, in particular to a method for image or video search reordering. Background technique
[0002] With the rapid development of information technology, a large number of multimedia data such as images and videos have emerged, which has become one of the important ways for people to obtain information. How to quickly and accurately obtain the information required by users from massive amounts of data is a challenging task. Image or video search re-ranking is the process of re-ranking the retrieval results by using the new ranking model to train the ranking model based on the initial text-based search results combined with other available auxiliary information. User experience and satisfaction.
[0003] There is a large amount of sorting information in the data related to multimedia retrieval. Sorting information refers to the supervisory information provided by the training data set ...
Examples
Embodiment Construction
[0046] In order to make the object, technical solution and advantages of the present invention clearer, the implementation manner of the present invention will be further described in detail below in conjunction with the accompanying drawings.
[0047] In order to improve retrieval accuracy, an embodiment of the present invention provides a method for image or video search reordering, see figure 1 , figure 2 with image 3 , see the description below:
[0048] The method provided by the embodiment of the present invention mainly constructs correlation graphs and irrelevant graphs according to the correlation level information of marked images or videos, and utilizes all image or video data to construct a global graph that maintains the local geometric properties between the data. A semi-supervised dimensionality reduction method in ranking learning to distinguish it from traditional dimensionality reduction methods based on class label information.
[0049] 101: Enter query...