A Method for Video Retrieval Using Compact Video Topic Descriptors
A video and topic technology, applied in the field of video retrieval using a compact video topic descriptor based on an undirected topic model, can solve problems such as being in the blank stage, and achieve robustness, discrimination, and interpretability Effect
Active Publication Date: 2016-08-17
INST OF AUTOMATION CHINESE ACAD OF SCI
View PDF2 Cites 0 Cited by
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Nevertheless, the current research on compact feature representation of the whole video is still in the blank stage
Method used
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View moreImage
Smart Image Click on the blue labels to locate them in the text.
Smart ImageViewing Examples
Examples
Experimental program
Comparison scheme
Effect test
Embodiment Construction
[0017] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with specific embodiments and with reference to the accompanying drawings.
[0018] The present invention learns a compact video topic descriptor based on an undirected topic model, and uses it for network video retrieval. By introducing non-negative real-valued hidden units and sparse constraint regularization items, the present invention extends the undirected topic model to make the learned topic descriptors more discriminative. At the same time, the present invention also provides an effective method to train the extended topic model.
[0019] figure 1 It is a flow chart of the method for video retrieval using compact video topic descriptors in the present invention, such as figure 1 As shown, the method includes the following steps:
[0020] Step S1, using part of the videos in the video d...
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More PUM
Login to View More Abstract
The invention discloses a method for performing video retrieval by compact video theme descriptors based on an undirected theme model. The method includes the steps: extracting local video features and acquiring BoW (bag of words) features of a video by the aid of a clustering algorithm; training the sparsely constrained non-negative undirected theme model by the aid of the BoW features of the video to learn theme features of the video; and deducing the theme descriptors of the video by the aid of the trained theme model and retrieving the video by calculating the cosine distance between the descriptors. By the method, low-dimensional and sparse video theme descriptors can be extracted from high-dimensional BoW features of the video, so that the retrieval efficiency of a large-scale database and a mobile search system with a limited bandwidth is greatly improved. Meanwhile, a theme feature structure of the video can be effectively mined by the theme model trained by the method, so that the extracted theme descriptors still have retrieval accuracy higher than that of original high-dimensional BoW features even if dimensions are low.
Description
technical field [0001] The invention relates to the field of pattern recognition and machine learning, in particular to a video retrieval method using a compact video topic descriptor based on an undirected topic model. Background technique [0002] In recent years, with the rapid development of the Internet and various multimedia terminals, the amount of video data uploaded to online video sites (such as Youku, YouTube) has grown exponentially, and most videos lack text annotations. Therefore, automatically learning compact video representations is crucial to improve the efficiency of content-based web video retrieval, especially in bandwidth-constrained mobile visual search systems. However, since online videos are often collected under uncontrolled conditions (for example, from different photographers and different devices), their content and clarity vary greatly. This makes the learning of video representations extremely challenging. [0003] Traditional multimedia ret...
Claims
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More Application Information
Patent Timeline
Login to View More Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30
Inventor 王亮谭铁牛黄永祯赵放
Owner INST OF AUTOMATION CHINESE ACAD OF SCI