Fast heuristic method to detect people in frontal depth images

This paper presents a new method for detecting people using only depth images captured by a camera in a frontal position. The approach is based on first detecting all the objects present in the scene and determining their average depth (distance to the camera). Next, for each object, a 3D Region of Interest (ROI) is processed around it in order to determine if the characteristics of the object correspond to the biometric characteristics of a human head. The results obtained using three public datasets captured by three depth sensors with different spatial resolutions and different operation principle (structured light, active stereo vision and Time of Flight) are presented. These results demonstrate that our method can run in realtime using a low-cost CPU platform with a high accuracy, being the processing times smaller than 1 ms per frame for a 512 × 424 image resolution with a precision of 99.26% and smaller than 4 ms per frame for a 1280 × 720 image resolution with a precision of 99.77%

People re-identification using depth and intensity information from an overhead sensor

This work presents a new people re-identification method, using depth and intensity images, both of them captured with a single static camera, located in an overhead position. The proposed solution arises from the need that exists in many areas of application to carry out identification and re-identification processes to determine, for example, the time that people remain in a certain space, while fulfilling the requirement of preserving people's privacy. This work is a novelty compared to other previous solutions, since the use of top-view images of depth and intensity allows obtaining information to perform the functions of identification and re-identification of people, maintaining their privacy and reducing occlusions. In the procedure of people identification and re-identification, only three frames of intensity and depth are used, so that the first one is obtained when the person enters the scene (frontal view), the second when it is in the central area of the scene (overhead view) and the third one when it leaves the scene (back view). In the implemented method only information from the head and shoulders of people with these three different perspectives is used. From these views three feature vectors are obtained in a simple way, two of them related to depth information and the other one related to intensity data. This increases the robustness of the method against lighting changes. The proposal has been evaluated in two different datasets and compared to other state-of-the-art proposal. The obtained results show a 96,7% success rate in re-identification, with sensors that use different operating principles, all of them obtaining depth and intensity information. Furthermore, the implemented method can work in real time on a PC, without using a GPU.Ministerio de Economía y CompetitividadAgencia Estatal de InvestigaciónUniversidad de Alcal

Effect of Carbamazepine, Ibuprofen, Triclosan and Sulfamethoxazole on Anaerobic Bioreactor Performance: Combining Cell Damage, Ecotoxicity and Chemical Information

Pharmaceuticals and personal care products (PPCPs) are partially degraded in wastewater treatment plants (WWTPs), thereby leading to the formation of more toxic metabolites. Bacterial populations in bioreactors operated in WWTPs are sensitive to different toxics such as heavy metals and aromatic compounds, but there is still little information on the effect that pharmaceuticals exert on their metabolism, especially under anaerobic conditions. This work evaluated the effect of selected pharmaceuticals that remain in solution and attached to biosolids on the metabolism of anaerobic biomass. Batch reactors operated in parallel under the pressure of four individual and mixed PPCPs (carbamazepine, ibuprofen, triclosan and sulfametoxazole) allowed us to obtain relevant information on anaerobic digestion performance, toxicological effects and alterations to key enzymes involved in the biodegradation process. Cell viability was quantitatively evaluated using an automatic analysis of confocal microscopy images, and showed that triclosan and mixed pollutants caused higher toxicity and cell death than the other individual compounds. Both individual pollutants and their mixture had a considerable impact on the anaerobic digestion process, favoring carbon dioxide production, lowering organic matter removal and methane production, which also produced microbial stress and irreversible cell damage.Comunidad de MadridUniversidad de Alcal

Towards Deep People Detection using CNNs Trained on Synthetic Images

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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

5to. Congreso Internacional de Ciencia, Tecnología e Innovación para la Sociedad. Memoria académica

El V Congreso Internacional de Ciencia, Tecnología e Innovación para la Sociedad, CITIS 2019, realizado del 6 al 8 de febrero de 2019 y organizado por la Universidad Politécnica Salesiana, ofreció a la comunidad académica nacional e internacional una plataforma de comunicación unificada, dirigida a cubrir los problemas teóricos y prácticos de mayor impacto en la sociedad moderna desde la ingeniería. En esta edición, dedicada a los 25 años de vida de la UPS, los ejes temáticos estuvieron relacionados con la aplicación de la ciencia, el desarrollo tecnológico y la innovación en cinco pilares fundamentales de nuestra sociedad: la industria, la movilidad, la sostenibilidad ambiental, la información y las telecomunicaciones. El comité científico estuvo conformado formado por 48 investigadores procedentes de diez países: España, Reino Unido, Italia, Bélgica, México, Venezuela, Colombia, Brasil, Estados Unidos y Ecuador. Fueron recibidas un centenar de contribuciones, de las cuales 39 fueron aprobadas en forma de ponencias y 15 en formato poster. Estas contribuciones fueron presentadas de forma oral ante toda la comunidad académica que se dio cita en el Congreso, quienes desde el aula magna, el auditorio y la sala de usos múltiples de la Universidad Politécnica Salesiana, cumplieron respetuosamente la responsabilidad de representar a toda la sociedad en la revisión, aceptación y validación del conocimiento nuevo que fue presentado en cada exposición por los investigadores. Paralelo a las sesiones técnicas, el Congreso contó con espacios de presentación de posters científicos y cinco workshops en temáticas de vanguardia que cautivaron la atención de nuestros docentes y estudiantes. También en el marco del evento se impartieron un total de ocho conferencias magistrales en temas tan actuales como la gestión del conocimiento en la universidad-ecosistema, los retos y oportunidades de la industria 4.0, los avances de la investigación básica y aplicada en mecatrónica para el estudio de robots de nueva generación, la optimización en ingeniería con técnicas multi-objetivo, el desarrollo de las redes avanzadas en Latinoamérica y los mundos, la contaminación del aire debido al tránsito vehicular, el radón y los riesgos que representa este gas radiactivo para la salud humana, entre otros

Reconstructing Native American Population History

The peopling of the Americas has been the subject of extensive genetic, archaeological and linguistic research; however, central questions remain unresolved1–5. One contentious issue is whether the settlement occurred via a single6–8 or multiple streams of migration from Siberia9–15. The pattern of dispersals within the Americas is also poorly understood. To address these questions at higher resolution than was previously possible, we assembled data from 52 Native American and 17 Siberian groups genotyped at 364,470 single nucleotide polymorphisms. We show that Native Americans descend from at least three streams of Asian gene flow. Most descend entirely from a single ancestral population that we call “First American”. However, speakers of Eskimo-Aleut languages from the Arctic inherit almost half their ancestry from a second stream of Asian gene flow, and the Na-Dene-speaking Chipewyan from Canada inherit roughly one-tenth of their ancestry from a third stream. We show that the initial peopling followed a southward expansion facilitated by the coast, with sequential population splits and little gene flow after divergence, especially in South America. A major exception is in Chibchan-speakers on both sides of the Panama Isthmus, who have ancestry from both North and South America