Video target detection method based on motion history image
A motion history image and target detection technology, applied in the field of video target detection based on motion history images, achieves the effects of fast speed, simple extraction, guaranteed detection speed and detection accuracy
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment 1
[0034] (1) The present invention uses a large-scale video target detection benchmark data set ImageNet VID proposed by the Large-Scale Visual Recognition Challenge in 2015 as an experimental data set, which contains 30 categories of targets. A subset of categories in the DET image dataset that takes into account different factors such as type of motion, video clutter, average number of object instances, and a few others can be extensively studied. Meanwhile, the dataset contains 3862 videos as training set, 555 videos as validation set, and 937 videos as test set. The training set and verification set have been fully labeled and all video clips have been cut into frames, that is, the data set is a sequence of video frames. The method in the present invention is not only applicable to the detection of vehicles and animals included in the data set, but also can be extended to other types of video target detection, such as pedestrian detection.
[0035] (2) The video frame can b...
Embodiment 2
[0053] The difference with embodiment 1 is:
[0054] The motion history image obtained in step 4 can first be processed with pseudo-color, that is, different colors are given according to the gray level of the pixels in the obtained gray-scale image, so that the motion history image can provide more information for model training. In the present invention, the grayscale color conversion method is adopted to convert the grayscale image into an RGB image, and the conversion method is as follows:
[0055] (1) Obtain the value f(x, y) of a certain pixel point (x, y) in the image;
[0056] (2) Obtain the value R(x, y) of the red channel, the value G(x, y) of the green channel, and the value B(x, y) of the blue channel of the pixel according to the following conversion formula.
[0057]
[0058]
[0059]
PUM
Abstract
Description
Claims
Application Information
- R&D Engineer
- R&D Manager
- IP Professional
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com