A Systematic Human Counting at Guest House using Sensing Device Technique

The application of vision detector using sensing device techniques is important in systematic counting of people both indoors and outdoors. This technique is broadly used in auditorium, lecture theatre and public market. In this paper, the technique uses a camera attached to an Android-based mobile phone which is then applied to capture images that are then transferred to a storage system via USB for image processing and counting. Also, a model for counting people indoors and outdoors is developed. Also, accurate human counting is observe

Iranian cashes recognition using mobile

In economical societies of today, using cash is an inseparable aspect of human life. People use cashes for marketing, services, entertainments, bank operations and so on. This huge amount of contact with cash and the necessity of knowing the monetary value of it caused one of the most challenging problems for visually impaired people. In this paper we propose a mobile phone based approach to identify monetary value of a picture taken from cashes using some image processing and machine vision techniques. While the developed approach is very fast, it can recognize the value of cash by average accuracy of about 95% and can overcome different challenges like rotation, scaling, collision, illumination changes, perspective, and some others.Comment: arXiv #13370

The Visual Social Distancing Problem

One of the main and most effective measures to contain the recent viral outbreak is the maintenance of the so-called Social Distancing (SD). To comply with this constraint, workplaces, public institutions, transports and schools will likely adopt restrictions over the minimum inter-personal distance between people. Given this actual scenario, it is crucial to massively measure the compliance to such physical constraint in our life, in order to figure out the reasons of the possible breaks of such distance limitations, and understand if this implies a possible threat given the scene context. All of this, complying with privacy policies and making the measurement acceptable. To this end, we introduce the Visual Social Distancing (VSD) problem, defined as the automatic estimation of the inter-personal distance from an image, and the characterization of the related people aggregations. VSD is pivotal for a non-invasive analysis to whether people comply with the SD restriction, and to provide statistics about the level of safety of specific areas whenever this constraint is violated. We then discuss how VSD relates with previous literature in Social Signal Processing and indicate which existing Computer Vision methods can be used to manage such problem. We conclude with future challenges related to the effectiveness of VSD systems, ethical implications and future application scenarios.Comment: 9 pages, 5 figures. All the authors equally contributed to this manuscript and they are listed by alphabetical order. Under submissio

Geometric and Physical Constraints for Drone-Based Head Plane Crowd Density Estimation

State-of-the-art methods for counting people in crowded scenes rely on deep networks to estimate crowd density in the image plane. While useful for this purpose, this image-plane density has no immediate physical meaning because it is subject to perspective distortion. This is a concern in sequences acquired by drones because the viewpoint changes often. This distortion is usually handled implicitly by either learning scale-invariant features or estimating density in patches of different sizes, neither of which accounts for the fact that scale changes must be consistent over the whole scene. In this paper, we explicitly model the scale changes and reason in terms of people per square-meter. We show that feeding the perspective model to the network allows us to enforce global scale consistency and that this model can be obtained on the fly from the drone sensors. In addition, it also enables us to enforce physically-inspired temporal consistency constraints that do not have to be learned. This yields an algorithm that outperforms state-of-the-art methods in inferring crowd density from a moving drone camera especially when perspective effects are strong.Comment: IROS 201

A Mobile Money Solution for Illiterate Users

Existing mobile money platforms have text based interfaces and target literate people. Illiterate people, without the assistance of literate individuals, cannot use such platforms. Applying user-centered requirements gathered in an Ethiopian context, this paper presents the design and development of a mobile money solution that targets illiterate people. Particular emphasis is given to how illiterate users deal with cash money in their everyday life and how such practices can be mapped into financial technology design. Given the ubiquity of mobile telephony in Africa, our solution is based on the widely available, relatively inexpensive and open source Android mobile web platform. The proposed system enables illiterate individuals to count money bills, while providing the facility to accept and make payments. In so doing, we provide an example of how a pervasive technology such as smartphones can empower a hitherto often neglected user category of illiterate users