Pedestrian monitoring techniques for crowd-flow prediction

The high concentration and flow rate of people in train stations during rush hours can pose a prominent risk to passenger safety and comfort. In situ counting systems are a critical element for predicting pedestrian flows in real time, and their capabilities must be rigorously tested in live environments. The focus of this paper is on evaluating the reliability of two alternative counting systems, the first using an array of infrared depth sensors and the second a visible light (RGB) camera. Both proposed systems were installed at a busy walkway in London Bridge station. The data were collected over a period of 2 months, after which, portions of the data set were labelled for quantitative evaluation against ground truth. In this paper, the implementation of the two different counting technologies is described, and the accuracy and limitations of both approaches under different conditions are discussed. The results show that the developed RGB-based system performs reliably across a wide range of conditions, while the depth-based approach proves to be a useful complement in conditions without significant ambient sunlight, such as underground passageways.EPSR

Towards dense people detection with deep learning and depth images

This paper describes a novel DNN-based system, named PD3net, that detects multiple people from a single depth image, in real time. The proposed neural network processes a depth image and outputs a likelihood map in image coordinates, where each detection corresponds to a Gaussian-shaped local distribution, centered at each person?s head. This likelihood map encodes both the number of detected people as well as their position in the image, from which the 3D position can be computed. The proposed DNN includes spatially separated convolutions to increase performance, and runs in real-time with low budget GPUs. We use synthetic data for initially training the network, followed by fine tuning with a small amount of real data. This allows adapting the network to different scenarios without needing large and manually labeled image datasets. Due to that, the people detection system presented in this paper has numerous potential applications in different fields, such as capacity control, automatic video-surveillance, people or groups behavior analysis, healthcare or monitoring and assistance of elderly people in ambient assisted living environments. In addition, the use of depth information does not allow recognizing the identity of people in the scene, thus enabling their detection while preserving their privacy. The proposed DNN has been experimentally evaluated and compared with other state-of-the-art approaches, including both classical and DNN-based solutions, under a wide range of experimental conditions. The achieved results allows concluding that the proposed architecture and the training strategy are effective, and the network generalize to work with scenes different from those used during training. We also demonstrate that our proposal outperforms existing methods and can accurately detect people in scenes with significant occlusions.Ministerio de Economía y CompetitividadUniversidad de AlcaláAgencia Estatal de Investigació

A Multi-Resident Number Estimation Method for Smart Homes

Population aging requires innovative solutions to increase the quality of life and preserve autonomous and independent living at home. A need of particular significance is the identification of behavioral drifts. A relevant behavioral drift concerns sociality: older people tend to isolate themselves. There is therefore the need to find methodologies to identify if, when, and how long the person is in the company of other people (possibly, also considering the number). The challenge is to address this task in poorly sensorized apartments, with non-intrusive sensors that are typically wireless and can only provide local and simple information. The proposed method addresses technological issues, such as PIR (Passive InfraRed) blind times, topological issues, such as sensor interference due to the inability to separate detection areas, and algorithmic issues. The house is modeled as a graph to constrain transitions between adjacent rooms. Each room is associated with a set of values, for each identified person. These values decay over time and represent the probability that each person is still in the room. Because the used sensors cannot determine the number of people, the approach is based on a multi-branch inference that, over time, differentiates the movements in the apartment and estimates the number of people. The proposed algorithm has been validated with real data obtaining an accuracy of 86.8%

A study on detection of risk factors of a toddler’s fall injuries using visual dynamic motion cues

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The research in this thesis is intended to aid caregivers’ supervision of toddlers to prevent accidental injuries, especially injuries due to falls in the home environment. There have been very few attempts to develop an automatic system to tackle young children’s accidents despite the fact that they are particularly vulnerable to home accidents and a caregiver cannot give continuous supervision. Vision-based analysis methods have been developed to recognise toddlers’ fall risk factors related to changes in their behaviour or environment. First of all, suggestions to prevent fall events of young children at home were collected from well-known organisations for child safety. A large number of fall records of toddlers who had sought treatment at a hospital were analysed to identify a toddler’s fall risk factors. The factors include clutter being a tripping or slipping hazard on the floor and a toddler moving around or climbing furniture or room structures. The major technical problem in detecting the risk factors is to classify foreground objects into human and non-human, and novel approaches have been proposed for the classification. Unlike most existing studies, which focus on human appearance such as skin colour for human detection, the approaches addressed in this thesis use cues related to dynamic motions. The first cue is based on the fact that there is relative motion between human body parts while typical indoor clutter does not have such parts with diverse motions. In addition, other motion cues are employed to differentiate a human from a pet since a pet also moves its parts diversely. They are angle changes of ellipse fitted to each object and history of its actual heights to capture the various posture changes and different body size of pets. The methods work well as long as foreground regions are correctly segmented

A study on detection of risk factors of a toddler's fall injuries using visual dynamic motion cues

The research in this thesis is intended to aid caregivers’ supervision of toddlers to prevent accidental injuries, especially injuries due to falls in the home environment. There have been very few attempts to develop an automatic system to tackle young children’s accidents despite the fact that they are particularly vulnerable to home accidents and a caregiver cannot give continuous supervision. Vision-based analysis methods have been developed to recognise toddlers’ fall risk factors related to changes in their behaviour or environment. First of all, suggestions to prevent fall events of young children at home were collected from well-known organisations for child safety. A large number of fall records of toddlers who had sought treatment at a hospital were analysed to identify a toddler’s fall risk factors. The factors include clutter being a tripping or slipping hazard on the floor and a toddler moving around or climbing furniture or room structures. The major technical problem in detecting the risk factors is to classify foreground objects into human and non-human, and novel approaches have been proposed for the classification. Unlike most existing studies, which focus on human appearance such as skin colour for human detection, the approaches addressed in this thesis use cues related to dynamic motions. The first cue is based on the fact that there is relative motion between human body parts while typical indoor clutter does not have such parts with diverse motions. In addition, other motion cues are employed to differentiate a human from a pet since a pet also moves its parts diversely. They are angle changes of ellipse fitted to each object and history of its actual heights to capture the various posture changes and different body size of pets. The methods work well as long as foreground regions are correctly segmented.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Towards a GIS-based Multiscale Visibility Assessment Method for Solar Urban Planning

Urban areas are facing a growing deployment of solar photovoltaic and thermal tech-nologies on building envelopes, both on roofs and on façades, essential for the realization of the Swiss Energy Strategy 2050. This process often occurs regardless of the desirable archi-tectural integration quality in a given urban context, which depends on socio-cultural sensitivi-ty and on the visibility of the solar modules from the public space. Visibility and visual impact are recurrent decisional factors in spatial planning processes, with practical implications in-cluding touristic and real estate promotion, outdoor human comfort, way finding, public feeling of security and advertisement. In this thesis, the definition of visibility under a geometrical, physical and psycho-physiological perspective is explored, several quantitative indicators being described and test-ed. The objective is to provide a scale-dependent methodology to assess the visibility of build-ing envelope surfaces exposed to solar radiation, which could host solar modules, in urban areas. A visibility index is determined for inclusion as a variable in a multi criteria method, cover-ing areas from the strategic broad territorial scale to the district level, including neighborhoods and clusters of buildings. Accomplished research includes the estimation of public visual inter-est on the basis of crowd-sourced photographic databases, complementing geometry-based parameters such as cumulative viewsheds and solid angles. At each scale, the visibility index is systematically overlapped on an urban sensitivity layer issued from land use and on a spatial representation of the solar energy generation potential, at an appropriate level of detail. Results indicate that stakeholders can reasonably expect to harvest a serious amount of solar energy by means of building integrated solar systems without crucially affecting public perception. In the study area located in the city of Geneva (Switzerland), more than 50 m2 / building of non-visible envelope surface receiving sufficient solar radiation for an economically viable solar re-furbishment is available over half of the buildings. Solar thermal collectors or PV panels in-stalled on scarcely visible surfaces, mainly situated in courtyards, far from the streets or in deep urban canyons, could cover about 10% of the annual heating demand or alternatively, the same share of electricity needs on a district basis. At the same time, plenty of highly visible areas remain available for high-end solar deployments, which could also serve pilot and demonstration purposes

Envisioning Transitions. Bodies, buildings, and boundaries

“Transition” is the dynamic process of changing state, going beyond, crossing over, and passing from one point to the next. The signification of the word is close to that of evolution, modification, mutation, and transformation, all of which are confined into a strictly restricted timeframe. Etymologically, “transitions” can be nothing else than temporary: they appear silently, burst, violently establish, and gradually disappear into reality. In their blinding momentariness, “transitions” bear with them the positive undertone of change and renewal, along with the hopefulness of that which is unknown.  If the term “transition” recurs regularly in the contemporary vocabulary of architecture and design cultures, this repetition reveals a period characterized by overlapping and sequential changes. The word is without a doubt overused, but not without reason. Indeed, we find ourselves in an unusually extended period of consecutive “transitions”, overwhelmingly undefined in temporality and ambitions. As we are witnessing societies go through stark demographic, political, economic, and cultural changes, the intersecting problematics (e.g., ecological, digital, pandemic, etc.) form a rather complex topography of change, negatively charged by the instability of dilated time and the uncertainty of undefined destination. The word is employed with the confidence of a natural process, as if it were a storm, and while we affirm our existence in “transition”, we nod our troubled times away. Whether positively or negatively perceived, “transitions” form bridges between histories. Yet, what does it actually mean to be in “transition”? Can we define it as an autonomous and productive period whose importance could go beyond a starting and an ending date? How are “transitions” impacting and being impacted by human spaces, the built environment, and design cultures? What are some concrete, practical case studies that demonstrate how “transitions” could affect architecture and design cultures while emphasizing the role that these disciplines play in transitional processes? It is within this backdrop that we put forward the theme of “transition”—in all its simplicity and complexity

Landscapes in Flux. Book of Proceedings

Peer reviewed proceedings ECLAS 2015 Conference|21 to 23 September| Department of Landscape Architecture, Estonian University of Life Sciences, Tartu, EstoniaEvery scientific paper published in these Conference Proceedings was peer reviewed. All explanations, data, results, etc. contained in this book have been made by authors to their best knowledge and were true and accurate at the time of publication. However, some errors could not be excluded, so neither the publisher, the editors, nor the authors can accept any legal responsibility or liability for any errors and omissions that may be made. © All rights reserved. No part of these proceedings may be reproduced by any means, electronic or mechanical, including photocopying, recording, or by any information storage and retrieval system, without permission in writing from the publisher.Department of Landscape Architecture, Estonian University of Life Sciences On behalf of European Council of Landscape Architecture Schools (ECLAS