Pyramidal Fisher Motion for Multiview Gait Recognition

The goal of this paper is to identify individuals by analyzing their gait. Instead of using binary silhouettes as input data (as done in many previous works) we propose and evaluate the use of motion descriptors based on densely sampled short-term trajectories. We take advantage of state-of-the-art people detectors to define custom spatial configurations of the descriptors around the target person. Thus, obtaining a pyramidal representation of the gait motion. The local motion features (described by the Divergence-Curl-Shear descriptor) extracted on the different spatial areas of the person are combined into a single high-level gait descriptor by using the Fisher Vector encoding. The proposed approach, coined Pyramidal Fisher Motion, is experimentally validated on the recent `AVA Multiview Gait' dataset. The results show that this new approach achieves promising results in the problem of gait recognition.Comment: Submitted to International Conference on Pattern Recognition, ICPR, 201

3D human pose estimation from depth maps using a deep combination of poses

Many real-world applications require the estimation of human body joints for higher-level tasks as, for example, human behaviour understanding. In recent years, depth sensors have become a popular approach to obtain three-dimensional information. The depth maps generated by these sensors provide information that can be employed to disambiguate the poses observed in two-dimensional images. This work addresses the problem of 3D human pose estimation from depth maps employing a Deep Learning approach. We propose a model, named Deep Depth Pose (DDP), which receives a depth map containing a person and a set of predefined 3D prototype poses and returns the 3D position of the body joints of the person. In particular, DDP is defined as a ConvNet that computes the specific weights needed to linearly combine the prototypes for the given input. We have thoroughly evaluated DDP on the challenging 'ITOP' and 'UBC3V' datasets, which respectively depict realistic and synthetic samples, defining a new state-of-the-art on them.Comment: Accepted for publication at "Journal of Visual Communication and Image Representation

Inverse central ordering for the Newton interpolation formula

An inverse central ordering of the nodes is proposed for the Newton interpolation formula. This ordering may improve the stability for certain distributions of nodes. For equidistant nodes, an upper bound of the conditioning is provided. This bound is close to the bound of the conditioning in the Lagrange interpolation formula, whose conditioning is the lowest. This ordering is related to a pivoting strategy of a matrix elimination procedure called Neville elimination. The results are illustrated with examples

The temporal dynamics of resource use by frugivorous birds: a network approach

Ecological network patterns are influenced by diverse processes that operate at different temporal rates. Here we analyzed whether the coupled effect of local abundance variation, seasonally phenotypic plastic responses, and species evolutionary adaptations might act in concert to shape network patterns. We studied the temporal variation in three interaction properties of bird species (number of interactions per species, interaction strength, and interaction asymmetry) in a temporal sequence of 28 plant frugivore interaction networks spanning two years in a Mediterranean shrubland community. Three main hypotheses dealing with the temporal variation of network properties were tested, examining the effects of abundance, switching behavior between alternative food resources, and morphological traits in determining consumer interaction patterns. Our results demonstrate that temporal variation in consumer interaction patterns is explained by short-term variation in resource and bird abundances and seasonal dietary switches between alternative resources (fleshy fruits and insects). Moreover, differences in beak morphology are associated with differences in switching behavior between resources, suggesting an important role of foraging adaptations in determining network patterns. We argue that beak shape adaptations might determine generalist and specialist feeding behaviors and thus the positions of consumer species within the network. Finally, we provide a preliminary framework to interpret phylogenetic signal in plant animal networks. Indeed, we show that the strength of the phylogenetic signal in networks depends on the relative importance of abundance, behavioral, and morphological variables. We show that these variables strongly differ in their phylogenetic signal. Consequently, we suggest that moderate and significant phylogenetic effects should be commonly observed in networks of species interactions. Read More: http://www.esajournals.org/doi/abs/10.1890/07-1939.

AIRPA: An Architecture to Support the Execution and Maintenance of AI-Powered RPA Robots

Robotic Process Automation (RPA) has quickly evolved from automating simple rule-based tasks. Nowadays, RPA is required to mimic more sophisticated human tasks, thus implying its combina tion with Artificial Intelligence (AI) technology, i.e., the so-called intelli gent RPA. Putting together RPA with AI leads to a challenging scenario since (1) it involves professionals from both fields who typically have different skills and backgrounds, and (2) AI models tend to degrade over time which affects the performance of the overall solution. This paper describes the AIRPA project, which addresses these challenges by proposing a software architecture that enables (1) the abstraction of the robot development from the AI development and (2) the monitor, con trol, and maintain intelligent RPA developments to ensure its quality and performance over time. The project has been conducted in the Serv inform context, a Spanish consultancy firm, and the proposed prototype has been validated with reality settings. The initial experiences yield promising results in reducing AHT (Average Handle Time) in processes where AIRPA deployed cognitive robots, which encourages exploring the support of intelligent RPA development.Ministerio de Ciencia, Innovación y Universidades PID2019-105455GB-C31Centro para el Desarrollo Tecnológico Industrial EXP00118029/IDI-20190524Centro para el Desarrollo Tecnológico Industrial P011-19/E0

El rol dels terpens en la competència entre plantes invasores i natives a Hawaii

Els terpens, hidrocarburs derivats de l'isoprè, són emesos i emmagatzemats per moltes plantes. La seva funció biològica i ecològica és estudiada des de fa uns anys, havent estat proposades diverses possibles funcions, com per exemple la protecció davant dels herbívors o com a mecanisme antiestrès metabòlic. Investigacions realitzades per científics del CREAF a les illes Hawaii han permès detectar diferències en l'acumulació foliar de terpens entre les espècies nadiues i invasives a través de l'screening efectuat en una àmplia mostra de les principals espècies forestals natives i invasives a l'illa d'Oahu. Aquests resultats aporten noves pistes per conèixer els mecanismes que expliquen l'èxit competitiu que permet que moltes espècies introduïdes en un nou hàbitat esdevinguin un problema ecològic per la seva expansió i exclusió competitiva d'espècies nadiues.Los terpenos, hidrocarburos derivados del isopreno, son emitidos y almacenados por muchas plantas. Su función biológica y ecológica está siendo estudiada desde hace unos años, habiendo sido propuestas varias posibles funciones, como por ejemplo la protección frente a los herbívoros o como mecanismo antiestrés metabólico. Investigaciones realizadas por científicos del CREAF en las islas Hawai han permitido detectar diferencias en la acumulación foliar de terpenos entre las especies nativas e invasivas a través del screening efectuado en una amplia muestra de las principales especies forestales nativas y invasivas en la Isla de Oahu. Estos resultados aportan nuevas pistas para conocer los mecanismos que explican el éxito competitivo que permite que muchas especies introducidas en un nuevo hábitat se conviertan en un problema ecológico por su expansión y exclusión competitiva de especies nativas

Design strategies for optimizing holographic optical tweezers setups

We provide a detailed account of the construction of a system of holographic optical tweezers. While much information is available on the design, alignment and calibration of other optical trapping configurations, those based on holography are relatively poorly described. Inclusion of a spatial light modulator in the setup gives rise to particular design trade-offs and constraints, and the system benefits from specific optimization strategies, which we discuss.Comment: 16 pages, 15 figure

HoloTrap: Interactive hologram design for multiple dynamic optical trapping

This work presents an application that generates real-time holograms to be displayed on a holographic optical tweezers setup; a technique that allows the manipulation of particles in the range from micrometres to nanometres. The software is written in Java, and uses random binary masks to generate the holograms. It allows customization of several parameters that are dependent on the experimental setup, such as the specific characteristics of the device displaying the hologram, or the presence of aberrations. We evaluate the software's performance and conclude that real-time interaction is achieved. We give our experimental results from manipulating 5 micron-diametre microspheres using the program.Comment: 17 pages, 6 figure

sSLAM: Speeded-Up Visual SLAM Mixing Artificial Markers and Temporary Keypoints

Environment landmarks are generally employed by visual SLAM (vSLAM) methods in the form of keypoints. However, these landmarks are unstable over time because they belong to areas that tend to change, e.g., shadows or moving objects. To solve this, some other authors have proposed the combination of keypoints and artificial markers distributed in the environment so as to facilitate the tracking process in the long run. Artificial markers are special elements (similar to beacons) that can be permanently placed in the environment to facilitate tracking. In any case, these systems keep a set of keypoints that is not likely to be reused, thus unnecessarily increasing the computing time required for tracking. This paper proposes a novel visual SLAM approach that efficiently combines keypoints and artificial markers, allowing for a substantial reduction in the computing time and memory required without noticeably degrading the tracking accuracy. In the first stage, our system creates a map of the environment using both keypoints and artificial markers, but once the map is created, the keypoints are removed and only the markers are kept. Thus, our map stores only long-lasting features of the environment (i.e., the markers). Then, for localization purposes, our algorithm uses the marker information along with temporary keypoints created just in the time of tracking, which are removed after a while. Since our algorithm keeps only a small subset of recent keypoints, it is faster than the state-of-the-art vSLAM approaches. The experimental results show that our proposed sSLAM compares favorably with ORB-SLAM2, ORB-SLAM3, OpenVSLAM and UcoSLAM in terms of speed, without statistically significant differences in accuracy.This research was funded by the project PID2019-103871GB-I00 of the Spanish Ministry of Economy, Industry and Competitiveness, FEDER, Project 1380047-F UCOFEDER-2021 of Andalusia and by the European Union–NextGeneration EU for requalification of Spanish University System 2021–2023