Pair Of People Research Articles

Social Distancing Detection Using Computer Vision

Abstract: SARS-CoV-19 is one of the deadliest pandemics the world has witnessed, taking around 6 crore lives till now across worldwide and about 6 lakhs in India. To limit its spread numerous countries have issued many safety measures. Due to the absence of the vaccine against the covid-19 the world has suffered a lot. Though scientists have developed several vaccines then also the pandemic is still out of control so therefore the only feasible option available to us is social distancing. We are implementing a Deep-learning based solution proposed for the above-stated problem. The distance between people can be estimated and the pair of people in the display will be indicated with red or green bounding boxes over it. The video frame from the camera was used as input, and the open-source object detection pre-trained model based on the YOLOv4 / YOLOv5 algorithm was employed for pedestrian detection. Later, the video frame was transformed into a top-down view for distance measurement from the 2D plane. The connection of CCTV cameras in public areas, public transportation, and hospitals is useful for gathering information. The proposed method was validated on a pre-recorded video of pedestrians walking on the street. Keywords: Deep learning, YOLOv4 / YOLOv5 algorithms, Social Distancing, Covid - 19

Social Distancing Detector Using Deep Learning

The paper presents a methodology for social distancing detection using deep learning to evaluate the distance between people to mitigate the impact of this coronavirus pandemic. The detection tool was developed to alert people to maintain a safe distance with each other by evaluating a video feed. The video frame from the camera was used as input, and the open-source object detection pre-trained model based on the YOLOv3 algorithm was employed for pedestrian detection. Later, the video frame was transformed into top-down view for distance measurement from the 2D plane. The distance between people can be estimated and any noncompliant pair of people in the display will be indicated with a red frame and red line. The proposed method was validated on a pre-recorded video of pedestrians walking on the street. The result shows that the proposed method is able to determine the social distancing measures between multiple people in the video. The developed technique can be further developed as a detection tool in real time application.

Piloting During a Pandemic

Key TakeawaysFour pilot teams shared experiences with piloting during the COVID‐19 pandemic, emphasizing that thoughtful planning streamlines the piloting process while mitigating the risk of transmitting illness.Remote access to and control of pilot equipment, along with the use of virtual communication platforms, enabled teams to successfully perform pilot‐scale studies.Operating pilot systems through the pandemic allowed teams to respond to drastic changes on a small scale to mitigate risks around full‐scale processes at the treatment plant.

A Combinatorial Question Related to an Easter Tradition Led to a New Entry in OEIS

In some regions of Bulgaria (at least) there is an Easter tradition, according to which in group of people first each one chooses a differently coloured egg, then each pair of people performs a swap (or swaps) by exchanging the eggs they currently have until everyone gets the originally chosen egg. This generates a natural question: if there are n people in the group, find the least number E(n) of swaps which makes this possible. We prove that E(n) is the least even number not less than n(n−1)/2. The sequence thus generated was added to the Online Encyclopedia of Integer Sequences and linked from there to several seemingly distant combinatorial results.

Risk assessment for HIV infection in men who have sex with men and the contribution of sexual partner networks.

This study aimed to evaluate the risk of HIV infection in men who have sex with men (MSM) by developing an index that considers sex partner networks. The index variables were age, ethnicity/skin color, schooling, relationship type, condom use in receptive and insertive relationships, self-perception of the possibility of HIV infection, sexually transmitted infections, and rapid HIV testing results. We used data from a cross-sectional MSM egocentric network survey conducted in Rio de Janeiro between 2014 and 2015. The initial research volunteer is called ego, each partner is called alter, and each pair of people in a relationship is called the dyad. Multiple logistic regression was used to define the coefficients of the equations for the elaboration of the indices. The index ranged from 0 to 1; the closer to 1, the higher the risk of HIV infection. HIV prevalence was 13.9% among egos. The mean egos index with an HIV-reactive test was 57% higher than non-reactive, and the same profile was observed in the index values of dyads. The index allowed the incorporation of network data through the dyads and contributed to the identification of individuals with a higher likelihood of acquiring HIV.

The speed of human social interaction perception

The ability to perceive others’ social interactions, here defined as the directed contingent actions between two or more people, is a fundamental part of human experience that develops early in infancy and is shared with other primates. However, the neural computations underlying this ability remain largely unknown. Is social interaction recognition a rapid feedforward process or a slower post-perceptual inference? Here we used magnetoencephalography (MEG) decoding to address this question. Subjects in the MEG viewed snapshots of visually matched real-world scenes containing a pair of people who were either engaged in a social interaction or acting independently. The presence versus absence of a social interaction could be read out from subjects’ MEG data spontaneously, even while subjects performed an orthogonal task. This readout generalized across different people and scenes, revealing abstract representations of social interactions in the human brain. These representations, however, did not come online until quite late, at 300 ​ms after image onset, well after feedforward visual processes. In a second experiment, we found that social interaction readout still occurred at this same late latency even when subjects performed an explicit task detecting social interactions. We further showed that MEG responses distinguished between different types of social interactions (mutual gaze vs joint attention) even later, around 500 ​ms after image onset. Taken together, these results suggest that the human brain spontaneously extracts information about others’ social interactions, but does so slowly, likely relying on iterative top-down computations.

Weakly supervised activity analysis with spatio-temporal localisation

In computer vision, an increasing number of weakly annotated videos have become available, due to the fact it is often difficult and time consuming to annotate all the details in the videos collected. Learning methods that analyse human activities in weakly annotated video data have gained great interest in recent years. They are categorised as “weakly supervised learning”, and usually form a multi-instance multi-label (MIML) learning problem. In addition to the commonly known difficulties of MIML learning, i.e. ambiguities in instances and labels, a weakly supervised method also has to cope with large data size, high dimensionality, and a large proportion of noisy examples usually found in video data. In this work, we propose a novel learning framework that iteratively optimises over a scalable MIML model and an instance selection process incorporating pairwise spatio-temporal smoothing during training. Such learned knowledge is then generalised to testing via a noise removal process based on the support vector data description algorithm. According to the experiments on three challenging benchmark video datasets, the proposed framework yields a more discriminative MIML model and less noisy training and testing data, and thus improves the system performance. It outperforms the state-of-the-art weakly supervised and even fully supervised approaches in the literature, in terms of annotating and detecting actions of a single person and interactions between a pair of people.

Families with Infants

Assume that a group of n people is going to an excursion and our task is to seat them into buses with several constraints each saying that a pair of people does not want to see each other in the same bus. This is a well-known graph coloring problem (with n being the number of vertices) and it can be solved in O *(2 n ) time by the inclusion-exclusion principle as shown by Björklund, Husfeldt, and Koivisto in 2009. Another approach to solve this problem in O *(2 n ) time is to use the Fast Fourier Transform (FFT). For this, given a graph G one constructs a polynomial P G ( x ) of degree O *(2 n ) with the following property: G is k -colorable if and only if the coefficient of x m (for some particular value of m ) in the k -th power of P ( x ) is nonzero. Then, it remains to compute this coefficient using FFT. Assume now that we have additional constraints: the group of people contains several infants and these infants should be accompanied by their relatives in a bus. We show that if the number of infants is linear, then the problem can be solved in O *((2 − ε) n ) time, where ε is a positive constant independent of n . We use this approach to improve known bounds for several NP-hard problems (the traveling salesman problem, the graph coloring problem, the problem of counting perfect matchings) on graphs of bounded average degree, as well as to simplify the proofs of several known results.

Perceiving Affordances for Aperture Passage in an Environment–Person–Person System

ABSTRACT The authors investigated the perception of affordances for aperture passage in an environment–person–person (E–P–P) system, which comprised an adult perceiver and a child as a companion. Perceivers were 8 large and 8 small female undergraduates and were companioned with 1 large and 1 small girl. The perceivers perceptually judged the minimum aperture width for the E–P–P system, and then the adult–child dyads (a pair of people) actually walked through to determine the system's actual minimum aperture width. Results demonstrated that perceivers precisely judged the action capabilities of an E–P–P system on the basis of the body-scaled information of each adult–child dyad. The findings extended the previous concept of affordances for an environment-person system to affordances for an E–P–P system.

Sectionable terraces and the (generalised) Oberwolfach problem

The generalised Oberwolfach problem requires v people to sit at s round tables of sizes l 1, l 2,…, l s (where l 1+ l 2+⋯+ l s = v) for successive meals in such a way that each pair of people are neighbours exactly λ times. The problem is denoted OP( λ; l 1, l 2,…, l s ) and if λ=1, which is the original problem, this is abbreviated to OP( l 1, l 2,…, l s ). It was known in 1892, though different terminology was then used, that a directed terrace with a symmetric sequencing for the cyclic group of order 2 n can be used to solve OP(2 n+1). We show how terraces with special properties can be used to solve OP(2; l 1, l 2) and OP( l 1, l 1, l 2) for a wide selection of values of l 1, l 2 and v. We also give a new solution to OP(2; l, l) that is based on Z 2l−1 . Solutions to the problem are also of use in the design of experiments, where solutions for tables of equal size are called resolvable balanced circuit Rees neighbour designs.

Models of the Small World

It is believed that almost any pair of people in the world can be connected to one another by a short chain of intermediate acquaintances, of typical length about six. This phenomenon, colloquially referred to as the “six degrees of separation,” has been the subject of considerable recent interest within the physics community. This paper provides a short review of the topic.