Research on Gesture Recognition and Denoising Technology of Electronic Information Teaching Demonstration Based on Kinect V2

Motion sensor is a kind of sensor which is commonly used in the field of human-computer interaction. This article uses Microsoft’s Kinect sensor to get in-depth information about gesture recognition in electronic instructional demonstrations. Here, we present the Kinect V2 sensor for use in demonstrating gesture capture and recognition in electronic information instruction. In this study, depth information is used to dynamically capture electronic information teaching demonstrative gestures. In addition, a combined denoising method is also proposed, which can effectively remove the interference and noise compared with the single denoising method. Then, the researchers programmed and moved the dynamic recognition of demonstrative gestures in electronic information instruction. Compared with some traditional denoising methods, the combined denoising method can effectively remove the blur and boundary burr. This study can be applied to the field of human-computer interaction in electronic information teaching to further improve the accuracy of information.

Dynamic Recognition and Tracking of Barium Flow Field Based on Deglutition Video

Dynamic fluoroscopy was used to study swallowing in 84 adult patients. We proposed a method to extract the barium contrast region by improved interframe difference method, and to indirectly determine the position of epigmatous cartilage and cricopharyngeal muscle according to the location of barium meal. The method is easy to understand, and the extraction effect is good, with 85% probability of successful extraction. On the other hand, in order to evaluate the degree of deglutition difficulty, we used calculation to evaluate variables including displacement, duration, residual quantity, etc., except that there were gender differences in variables and external factors, such as illumination, most of the measurement variables had very good reliability. The experimental results showed that the moving target fluid barium was extracted by quantifying dynamic fluorescence deglutition and using gaussian based background subtraction algorithm. We conclude that this approach significantly reduces the time it takes clinicians to examine moving images. This paper describes how to study swallowing disorders by X-ray barium fluoroscopy, explains the application of interframe difference algorithm and background subtraction in deglutiography, and extracts the residual amounts in three locations: oral cavity, epiglottic cartilage and piriform fosse.

Logical-Combinatorial Approaches in Dynamic Recognition Problems

A pattern recognition scenario, where instead of object classification into the classes by the learning set, the algorithm aims to allocate all objects to the same, the so-called "normal" class, is the research objective. Given the learning set L; the class K0 is called “normal”, and the reminder l classes K1, K2, ... , Kl from the environment K are “deviated”. The classification algorithm is for a recurrent use in a "classification, action" format. Actions Ai are defined for each “deviated” class Ki. Applied to an object x ∈ Ki, the action delivers update Ai(x) of the object. The goal is in constructing a classification algorithm A that applied repeatedly (small number of times) to the objects of L, moves the objects (correspondingly, the elements of K) to the “normal” class. In this way, the static recognition action is transferred to a dynamic domain. This paper is continuing the discussion on the “normal” class classification problem, its theoretical postulations, possible use cases, and advantages of using logical-combinatorial approaches in solving these dynamic recognition problems. Some light relation to the topics like reinforcement learning, and recurrent neural networks are also provided.