Fast lens boundary detection method

A lens boundary detection and lens technology, which is used in special data processing applications, instruments, electrical digital data processing, etc.

Inactive Publication Date: 2008-08-06
BEIHANG UNIV
View PDF0 Cites 17 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, most of the video frames to be compared are internal video frames of the shot, so repeated calculation and comparison are unnecessary, and the processing speed of shot boundary detection is greatly reduced

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 more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Fast lens boundary detection method
  • Fast lens boundary detection method
  • Fast lens boundary detection method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0015] As shown in Figure 1, the fast shot boundary detection method of the present invention comprises the following steps:

[0016] 1. Streamline the video sequence.

[0017] (1) First convert the OSF into a grayscale sequence according to the following formula.

[0018] f(x,y,t)=0.299*r(x,y,t)+0.587*g(x,y,t)+0.114*b(x,y,t) (1)

[0019] Among them, f(x, y, t) represents the grayscale image of the video sequence, r(x, y, t), g(x, y, t) and b(x, y, t) represent the original video frame R, G, B components. Extract the grayscale variance from the grayscale sequence to get the variance sequence σ 2 (t).

[0020] (2) Calculate σ according to the following formula 2 (t) to obtain the difference value sequence D(t) of gray variance.

[0021] D(t)=|σ 2 (t)-σ 2 (t+1)| (2)

[0022] Analysis of the gray variance variance value sequence D(t) shows that at the lens cut, D(t) will have a single peak; and at the lens gradient, D(t) will have a continuous peak, as shown in Figure 2....

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

No PUM Login to view more

Abstract

The invention provides a method for quickly detecting a shot boundary, comprising the following steps that: firstly, a video frame inside a lens is removed from an original frame sequence OFS to obtain a recorded frame sequence RFS according to changes of a brightness variance feature of the video frame; meanwhile, a partial lens gradation existed in a video is determined according to a concave shaped parabola of the brightness variance feature; then, a pixel pair difference, a color histogram difference feature, an edge histogram difference feature and so on are selected from the RFS as accordances for a video continuity detection; then, a support vector machine is adopted to perform a shot cut detection; finally, the shot cut detection is performed for the rest video sequence by adopting a method of reducing temporal resolution. The method for quickly detecting a shot boundary improves the processing speed for the shot boundary detection, and guarantees a recall ratio and the accuracy of an operation at the same time.

Description

technical field [0001] The invention belongs to the field of video content analysis, and in particular relates to a method for quickly detecting the boundary of a shot. Background technique [0002] Shot boundary detection is the first step in video content analysis and retrieval. The shot boundary detection process can be abstracted into three basic steps, which are video feature extraction, feature continuity detection and continuity detection result classification. Among them, the video feature extraction is to extract the feature vector from the video to represent the video content; the feature continuity detection is to compare the video features to determine whether the features of adjacent videos are continuous; the continuity detection result classification is responsible for the continuity detection results A decision is made to ultimately determine the presence and type of shot boundaries. [0003] So far, there have been many studies on shot boundary detection, ...

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
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06F17/30
Inventor 薛玲李超李欢钟林熊璋
Owner BEIHANG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap