Intelligent field recording board applied to college course recording and classification method after recording

Abstract

The invention discloses an intelligent field recording board applied to college course recording, which comprises a central processing unit, a camera, a patting rod and a plate body, wherein the camera is connected with the central processing unit; the patting rod is connected with the camera; the plate body is connected with the patting rod; and the central processing unit is in wireless connection with course recording equipment through a wireless communication module. According to the field recording board and the method in the invention, the field recording board is creatively applied to the course recording process; a photo is shot through the field recording board, so that accurate recording of the course information is achieved; a power supply and a touch display screen are arrangedon the field recording board, and the applicability to various scenes is improved; the photo and the course video shot by the field recording board are saved to the same folder, and convenience is brought to video proofreading in the later stage; and the accuracy of a classification result is guaranteed through comparison of audios and videos.

Description

technical field [0001] The invention belongs to the technical field of network teaching, and specifically relates to an intelligent slate applied to course recording in colleges and universities and a classification method after recording. Background technique [0002] In motion picture and video production, slates are commonly used to synchronize picture and sound. Slates are also used to identify and mark specific takes and shots recorded during production. Conventional techniques have been developed to generate and record timecode during the production of movies or videos. [0003] The rapid development of China's online course market is also due to the gradual networking of knowledge resources. Information covers users in a huge information network and greatly improves everyone's ability to acquire knowledge. However, in the process of course shooting, the workload of shooting every day is very large. Correspondingly, the workload of post-production video classificatio...

AI Technical Summary

Problems solved by technology

However, in the process of course shooting, the workload of shooting every day is very large. Correspondingly, the workload of post-production video classification is also quite heavy. At present, post-production video classification still relies on manual work, which is inefficient and has a wide variety of courses. The pre-shooting and post-production personnel Communication is prone to information transmission deviations. If a video recognition system is built to recognize each video, the cost is too high, and the recognition results cannot be guaranteed

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