Bionic robot peacock image identification method based on deep learning

Abstract

The invention discloses a bionic robot peacock image identification method based on deep learning. The method comprises the following steps that: collecting a public face detection database as an image dataset for training and verification; designing deep learning architecture based on a convolutional neural network, and realizing a face detection function in the deep learning architecture; collecting a site image shot by a bionic robot peacock camera to fine tuning on the trained convolutional neural network to realize the face detection function under an indoor complex environment; and obtaining an empirical parameter to determine the dressing positioning of an audience, and carrying out statistics on the corresponding proportion of various colors. By use of the method, the accurate andefficient face detection and color identification of the recreational bionic robot under the complex environment can be realized, and robustness is high; in addition, for the site image, carrying outparameter fine tuning on the trained deep learning architecture; and finally, carrying out real-time face detection and dressing identification on the site image captured by the camera. The method canbe applied to science and technology museums, hotels and shops for tourists to visit and amuse.

Description

technical field [0001] The invention relates to the technical field of computer identification, in particular to a bionic machine peacock image identification method based on deep learning. Background technique [0002] Bionic robot is a combination of bionics and application requirements in the field of robotics. From the perspective of robots, bionic robots are an advanced stage of robot development, and biological characteristics provide many useful references for robot design. There are many types of bionic robots, such as bionic robot fish and bionic robot dogs. And widely used in military and industrial fields, but the application as entertainment robot is less at present. The vision system is an important part of the bionic robot, which is equivalent to the "eyes" of the bionic robot. The system generally captures the surrounding environment information through a high-definition camera placed on the robot, and analyzes and processes the captured image through the e...

AI Technical Summary

Problems solved by technology

Although specific image features have achieved good results in the field of bionic robots, traditional image features rely more on human experience, and in complex environments, the complexity of feature extraction is high and the robustness is low.

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