Academic literature on the topic 'FP (FIRST PERSON) AND TP (THIRD PERSON)'

Abstract Gait recognition, which allows to recognise someone from a distance, has a lot of applications. The gait of a person is commonly used as a biometric approach to identify or categorise them by gender and age. Biometric systems are a fast-growing subject that necessitates the development of creative solutions to problems that have plagued previous attempts. By initially looking at the design of a gait detection system, two different types of gait datasets have been reported and presented in this paper. While running at the same time, the first person (FP) data containing the camera motion gathered from the movement of the volunteer’s body and the third person (TP) data captured from a distant view were recorded. The dataset contains a total of 23 participants (14 males and 9 females). The discussion is expanded to include a comparison of the results obtained using TP and FP data, as well as an examination of the physiological motions recorded while running and walking.

In the article, the author examines two relatively new gastronomic trends, such as functional and personalized types of nutrition. As follows from the names, the directions pursue the goals of ensuring the functioning (of the organism) and compliance with the lifestyle (of a person). Considering functional nutrition (AF), it should be noted that, aimed primarily at ensuring, first of all, the vital activity of the body as a whole, this direction leads to the need to use specific products and follow certain traditions. Despite the fact that such a nutrition strategy has come to the fore today, it is not something new, since even in Soviet times the foundations of functional nutrition were laid in the form of rationalization of food consumption by the population through a network of state catering establishments. The introduced culture of consumption, with varying success, became a symbol of the Soviet era, which, of course, was influenced by the government of the USSR with its ideology of a perfectly functioning organism of the working man, the sufficiency of nutrition in the Soviet Union and the rejection of home cooking as a “hotbed of the bourgeoisie”. Meanwhile, today the FP once again occupies a leading position among the tools and means of a healthy lifestyle, but without political and ideological background. However, functional nutrition, as a rule, does not take into account individual characteristics of a person. As an example of such a diet and, in general, a culture of consumption (with a certain time and place), organized meals in kindergartens and schools can be cited. Thus, there is a need for individual accounting of the sufficiency (or insufficiency) of the volume of food components consumed. This is personalized nutrition, which takes into account a person’s lifestyle, that is, nutrition recommendations are based on his genetic inheritance, anamnesis, energy consumption, gender, activity level, daily activity characteristics, etc. Individualized nutrition creates prerequisites for the development of various technologies in the food industry, digital technologies, etc. The author believes that it is expedient and fair to single out the third gastronomic direction – functionally personalized nutrition, which takes into account both components at once. In this regard, at the same time, nutritionology is developing as a science and a type of practical activity related to the organization of functionally personalized human nutrition. In addition, the growth of the need for this strategy will lead to a change in the structure of the offer in the field of gastronomy, forms of everyday life associated with food consumption.

IntroductionBrain-machine interfaces (BMIs) attempt to establish communication between the user and the device to be controlled. BMIs have great challenges to face in order to design a robust control in the real field of application. The artifacts, high volume of training data, and non-stationarity of the signal of EEG-based interfaces are challenges that classical processing techniques do not solve, showing certain shortcomings in the real-time domain. Recent advances in deep-learning techniques open a window of opportunity to solve some of these problems. In this work, an interface able to detect the evoked potential that occurs when a person intends to stop due to the appearance of an unexpected obstacle has been developed.Material and methodsFirst, the interface was tested on a treadmill with five subjects, in which the user stopped when an obstacle appeared (simulated by a laser). The analysis is based on two consecutive convolutional networks: the first one to discern the intention to stop against normal walking and the second one to correct false detections of the previous one.Results and discussionThe results were superior when using the methodology of the two consecutive networks vs. only the first one in a cross-validation pseudo-online analysis. The false positives per min (FP/min) decreased from 31.8 to 3.9 FP/min and the number of repetitions in which there were no false positives and true positives (TP) improved from 34.9% to 60.3% NOFP/TP. This methodology was tested in a closed-loop experiment with an exoskeleton, in which the brain-machine interface (BMI) detected an obstacle and sent the command to the exoskeleton to stop. This methodology was tested with three healthy subjects, and the online results were 3.8 FP/min and 49.3% NOFP/TP. To make this model feasible for non-able bodied patients with a reduced and manageable time frame, transfer-learning techniques were applied and validated in the previous tests, and were then applied to patients. The results for two incomplete Spinal Cord Injury (iSCI) patients were 37.9% NOFP/TP and 7.7 FP/min.

In this study, past participle agreement (PPA) patterns in French and Italian are explained based on recent minimalist notions involving minimal search and labeling. For minimal computation, Agree minimally values a participle and an in-situ object (Minimal Agree). Hence, the participle is spelled out in a default form. If an object is displaced, a participle can choose to Agree with the object’s copy in its SPEC. Since the Agree operation is coupled with labeling, it fully values the participle (Full Agree), resulting in morphological agreement. In many cases, the optionality of PPA results from the participle’s free selection between the two types of Agree. The proposed analysis also deals with cases where PPA is either obligatory or absent. First, a derived subject obligatorily triggers agreement since Full Agree applies to the subject to label the so-called TP node, which also affects the participle. Second, Italian 3rd person clitic objects control agreement obligatorily, which is attributed to their internal structure. Third, agreement with a wh-object is absent in Italian because of criterial freezing. Since Full Agree is part of criterial licensing, a wh-phrase cannot select this option until it reaches its final criterial position unless some form of reconstruction is available.

The gait of a person is often used as a biometric tool to identify or classify a person based on gender and age. Because of its ability to track a person from afar, gait recognition has found use in a variety of fields, including forensics, surveillance, and health monitoring departments. Biometric systems is a rapidly emerging area that necessitates the development of new methods to address problems that have plagued previous approaches. Human gait is a less-explored region in the field of biometrics. In this Project, two different types of gait datasets have been reported and presented. The FP (First Person) data carrying the camera motion collected from the movement of the volunteer's body and the TP (Third Person) data captured from a distant view were recorded at the same time. A total of 24 subjects (15 males and 9 females) are included in the dataset. The discussion is extended to include a comparison of the results obtained using TP and FP data. This report also provides an extensive survey of the stages involved in the framework of gait recognition by analysing the different methods used in each stage along with the description of the feature extraction process and the state-of-the-art techniques used in appearance-based and human-pose-based methods. Moreover, a brief comparative description on the recent data reduction or feature selection methods has been provided. Furthermore, it will provide a first-hand knowledge about the public datasets that is motion capture databases and the datasets simply used for human gait recognition. In comparison to other biometric methods, gait recognition has a lot of potential for future work, Researchers working in the fields of biometrics, human pose estimation, monitoring, human gait recognition and analysis will benefit from the review given in the survey.