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Video image recognition system and method based on deep learning

A video image and deep learning technology, which is applied in the field of video image recognition system based on deep learning, can solve the problems of low image recognition accuracy, complex processing model, long reasoning time, etc., to improve the effect of gesture classification recognition and accurate image recognition The effect of high degree and good generalization performance

Inactive Publication Date: 2019-12-10
FUJIAN ZHONGKE YACHUANG COMM TECH CO LTD
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  • Summary
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the existing technical solutions, the processing model is complicated, the reasoning time is long, the cost is high, the processing speed is slow, and the image recognition accuracy is low

Method used

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  • Video image recognition system and method based on deep learning
  • Video image recognition system and method based on deep learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0053] Such as figure 1 As shown, the video image recognition method based on deep learning includes:

[0054] Step 1, collecting video information and first picture information, decomposing the video information into multiple continuous single-frame pictures, and obtaining second picture information;

[0055] Step 2. Input the first picture information and / or the second picture information into the clustering model for cluster classification; determine the cluster center of each type of posture, and divide each type of posture samples into subsets;

[0056] Step 3. According to the divided subsets, optimize the neural network model with the training strategy of course learning;

[0057] Step 4: Receive the image information to be recognized, and use the optimized neural network model to perform gesture recognition.

[0058] In this embodiment, by clustering and classifying the first picture information and / or the second picture information, the training strategy of course l...

Embodiment 2

[0091] Such as figure 2 As shown, the video image recognition system based on deep learning includes:

[0092] Acquisition module 1, the acquisition module 1 collects video information and first picture information, decomposes video information into multiple continuous single-frame pictures, and obtains second picture information;

[0093] Cluster classification module 2, described cluster classification module 2 inputs the first picture information and / or the second picture information, utilizes clustering model to carry out cluster classification; Determine the cluster center of each class attitude, and each class attitude sample partition subsets;

[0094] Training optimization module 3, said training optimization module 3 optimizes the neural network model with the training strategy of course learning according to the subsets divided;

[0095] Gesture recognition module 4, the gesture recognition module 4 receives the picture information to be recognized, and uses the o...

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Abstract

The invention relates to a video image recognition system and method based on deep learning, and the method comprises the following steps: collecting video information and first picture information, decomposing the video information into a plurality of continuous single-frame pictures, and obtaining second picture information; inputting the first picture information and / or the second picture information into a clustering model for clustering classification; determining a clustering center of each type of attitude, and dividing each type of attitude sample into subsets; optimizing a neural network model by using a training strategy of course learning according to the divided subsets; and receiving to-be-identified picture information, and performing attitude identification by using the optimized neural network model. Compared with the prior art, the invention has the advantages that more effective features with more distinguishing strength can be extracted, so that the trained classifier has better generalization performance, the processing speed is high, the posture classification and recognition effect is improved, and the picture recognition accuracy is high.

Description

technical field [0001] The present invention relates to the technical field of video image recognition, in particular to a video image recognition system and method based on deep learning. Background technique [0002] Human body posture recognition refers to the automatic analysis and processing of the human body in the image, and the human body posture information is marked according to the pre-designed classification. Gesture recognition is a basic problem in behavior recognition. Reliable and accurate recognition of human posture can be used for human behavior analysis, identification of personnel working status or learning status, and thus automatically provide information for intelligent management of various industries. [0003] In the prior art, a student sitting posture detection and correction system based on image recognition with application number 201710395795.4 includes a face image detection module for detecting face images entering the shooting area; a face p...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/10G06F18/23G06F18/24
Inventor 李家志常磊
Owner FUJIAN ZHONGKE YACHUANG COMM TECH CO LTD
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