Temporal and phylogenetic evolution of the sauropod dinosaur body plan

The colossal size and body plan of sauropod dinosaurs are unparalleled in terrestrial vertebrates. However, to date, there have been only limited attempts to examine temporal and phylogenetic patterns in the sauropod bauplan. Here, we combine three-dimensional computational models with phylogenetic reconstructions to quantify the evolution of whole-body shape and body segment properties across the sauropod radiation. Limitations associated with the absence of soft tissue preservation in fossils result in large error bars about mean absolute body shape predictions. However, applying any consistent skeleton : body volume ratio to all taxa does yield changes in body shape that appear concurrent with major macroevolutionary events in sauropod history. A caudad shift in centre-of-mass (CoM) in Middle Triassic Saurischia, associated with the evolution of bipedalism in various dinosaur lineages, was reversed in Late Triassic sauropodomorphs. A craniad CoM shift coincided with the evolution of quadrupedalism in the Late Triassic, followed by a more striking craniad shift in Late Jurassic–Cretaceous titanosauriforms, which included the largest sauropods. These craniad CoM shifts are strongly correlated with neck enlargement, a key innovation in sauropod evolution and pivotal to their gigantism. By creating a much larger feeding envelope, neck elongation is thought to have increased feeding efficiency and opened up trophic niches that were inaccessible to other herbivores. However, we find that relative neck size and CoM position are not strongly correlated with inferred feeding habits. Instead the craniad CoM positions of titanosauriforms appear closely linked with locomotion and environmental distributions, potentially contributing to the continued success of this group until the end-Cretaceous, with all other sauropods having gone extinct by the early Late Cretaceous

Adaptive Silhouette Extraction In Dynamic Environments Using Fuzzy Logic

Extracting a human silhouette from an image is the enabling step for many high-level vision processing tasks, such as human tracking and activity analysis. In a previous paper, we addressed some of the challenges in silhouette extraction and human tracking in a real-world unconstrained environment where the background is complex and dynamic. We extracted features from image regions, accumulated the feature information over time, fused high-level knowledge with low-level features, and built a time-varying background model. A problem with our system is that by adapting the background model, objects moved by a human are difficult to handle. In order to reinsert them into the background, we run the risk of cutting off part of the human silhouette, such as in a quick arm movement. In this paper, we develop a fuzzy logic inference system to detach the silhouette of a moving object from the human body. Our experimental results demonstrate that the fuzzy inference system is very efficient and robust.The authors are grateful for the support from NSF ITR grant IIS-0428420 and the U.S. Administration on Aging, under grant 90AM3013

Single camera pose estimation using Bayesian filtering and Kinect motion priors

Traditional approaches to upper body pose estimation using monocular vision rely on complex body models and a large variety of geometric constraints. We argue that this is not ideal and somewhat inelegant as it results in large processing burdens, and instead attempt to incorporate these constraints through priors obtained directly from training data. A prior distribution covering the probability of a human pose occurring is used to incorporate likely human poses. This distribution is obtained offline, by fitting a Gaussian mixture model to a large dataset of recorded human body poses, tracked using a Kinect sensor. We combine this prior information with a random walk transition model to obtain an upper body model, suitable for use within a recursive Bayesian filtering framework. Our model can be viewed as a mixture of discrete Ornstein-Uhlenbeck processes, in that states behave as random walks, but drift towards a set of typically observed poses. This model is combined with measurements of the human head and hand positions, using recursive Bayesian estimation to incorporate temporal information. Measurements are obtained using face detection and a simple skin colour hand detector, trained using the detected face. The suggested model is designed with analytical tractability in mind and we show that the pose tracking can be Rao-Blackwellised using the mixture Kalman filter, allowing for computational efficiency while still incorporating bio-mechanical properties of the upper body. In addition, the use of the proposed upper body model allows reliable three-dimensional pose estimates to be obtained indirectly for a number of joints that are often difficult to detect using traditional object recognition strategies. Comparisons with Kinect sensor results and the state of the art in 2D pose estimation highlight the efficacy of the proposed approach.Comment: 25 pages, Technical report, related to Burke and Lasenby, AMDO 2014 conference paper. Code sample: https://github.com/mgb45/SignerBodyPose Video: https://www.youtube.com/watch?v=dJMTSo7-uF

Contour Generator Points for Threshold Selection and a Novel Photo-Consistency Measure for Space Carving

Space carving has emerged as a powerful method for multiview scene reconstruction. Although a wide variety of methods have been proposed, the quality of the reconstruction remains highly-dependent on the photometric consistency measure, and the threshold used to carve away voxels. In this paper, we present a novel photo-consistency measure that is motivated by a multiset variant of the chamfer distance. The new measure is robust to high amounts of within-view color variance and also takes into account the projection angles of back-projected pixels. Another critical issue in space carving is the selection of the photo-consistency threshold used to determine what surface voxels are kept or carved away. In this paper, a reliable threshold selection technique is proposed that examines the photo-consistency values at contour generator points. Contour generators are points that lie on both the surface of the object and the visual hull. To determine the threshold, a percentile ranking of the photo-consistency values of these generator points is used. This improved technique is applicable to a wide variety of photo-consistency measures, including the new measure presented in this paper. Also presented in this paper is a method to choose between photo-consistency measures, and voxel array resolutions prior to carving using receiver operating characteristic (ROC) curves

Size and Shape Determination of Riprap and Large-sized Aggregates Using Field Imaging

Riprap rock and large-sized aggregates are extensively used in transportation, geotechnical, and hydraulic engineering applications. Traditional methods for assessing riprap categories based on particle weight may involve subjective visual inspection and time-consuming manual measurements. Aggregate imaging and segmentation techniques can efficiently characterize riprap particles for their size and morphological/shape properties to estimate particle weights. Particle size and morphological/shape characterization ensure the reliable and sustainable use of all aggregate skeleton materials at quarry production lines and construction sites. Aggregate imaging systems developed to date for size and shape characterization, however, have primarily focused on measurement of separated or non-overlapping aggregate particles. This research study presents an innovative approach for automated segmentation and morphological analyses of stockpile aggregate images based on deep-learning techniques. As a project outcome, a portable, deployable, and affordable field-imaging system is envisioned to estimate volumes of individual riprap rocks for field evaluation. A state-of-the-art object detection and segmentation framework is used to train an image-segmentation kernel from manually labeled 2D riprap images in order to facilitate automatic and user-independent segmentation of stockpile aggregate images. The segmentation results show good agreement with ground-truth validation, which entailed comparing the manual labeling to the automatically segmented images. A significant improvement to the efficiency of size and morphological analyses conducted on densely stacked and overlapping particle images is achieved. The algorithms are integrated into a software application with a user-friendly Graphical User Interface (GUI) for ease of operation. Based on the findings of this study, this stockpile aggregate image analysis program promises to become an efficient and innovative application for field-scale and in-place evaluations of aggregate materials. The innovative imaging-based system is envisioned to provide convenient, reliable, and sustainable solutions for the on-site quality assurance/quality control (QA/QC) tasks related to riprap rock and large-sized aggregate material characterization and classification.IDOT-R27-182Ope

Ecological opportunity and the rise and fall of crocodylomorph evolutionary innovation

Understanding the origin, expansion and loss of biodiversity is fundamental to evolutionary biology. The approximately 26 living species of crocodylomorphs (crocodiles, caimans, alligators and gharials) represent just a snapshot of the group's rich 230-million-year history, whereas the fossil record reveals a hidden past of great diversity and innovation, including ocean and land-dwelling forms, herbivores, omnivores and apex predators. In this macroevolutionary study of skull and jaw shape disparity, we show that crocodylomorph ecomorphological variation peaked in the Cretaceous, before declining in the Cenozoic, and the rise and fall of disparity was associated with great heterogeneity in evolutionary rates. Taxonomically diverse and ecologically divergent Mesozoic crocodylomorphs, like marine thalattosuchians and terrestrial notosuchians, rapidly evolved novel skull and jaw morphologies to fill specialized adaptive zones. Disparity in semi-aquatic predatory crocodylians, the only living crocodylomorph representatives, accumulated steadily, and they evolved more slowly for most of the last 80 million years, but despite their conservatism there is no evidence for long-term evolutionary stagnation. These complex evolutionary dynamics reflect ecological opportunities, that were readily exploited by some Mesozoic crocodylomorphs but more limited in Cenozoic crocodylians.Sampling. We sample 240 crocodylomorph skulls and 204 lower jaws Shape analyses. Disparity was quantified using 2-D geometric morphometrics, with a mixed landmark/semi-landmarks approach. Phylogeny. A composite crocodylomorph supertree was assembled . Disparity. Disparity was quantified using custom code and the R package dispRity. Evolutionary rates. Rates of evolution were analysed in a Bayesian framework based on the multivariate variable-rates model in BayesTraits

A fast and robust hand-driven 3D mouse

The development of new interaction paradigms requires a natural interaction. This means that people should be able to interact with technology with the same models used to interact with everyday real life, that is through gestures, expressions, voice. Following this idea, in this paper we propose a non intrusive vision based tracking system able to capture hand motion and simple hand gestures. The proposed device allows to use the hand as a "natural" 3D mouse, where the forefinger tip or the palm centre are used to identify a 3D marker and the hand gesture can be used to simulate the mouse buttons. The approach is based on a monoscopic tracking algorithm which is computationally fast and robust against noise and cluttered backgrounds. Two image streams are processed in parallel exploiting multi-core architectures, and their results are combined to obtain a constrained stereoscopic problem. The system has been implemented and thoroughly tested in an experimental environment where the 3D hand mouse has been used to interact with objects in a virtual reality application. We also provide results about the performances of the tracker, which demonstrate precision and robustness of the proposed syste

Vision-based traffic surveys in urban environments

This paper presents a state-of-the-art, vision-based vehicle detection and type classification to perform traffic surveys from a roadside closed-circuit television camera. Vehicles are detected using background subtraction based on a Gaussian mixture model that can cope with vehicles that become stationary over a significant period of time. Vehicle silhouettes are described using a combination of shape and appearance features using an intensity-based pyramid histogram of orientation gradients (HOG). Classification is performed using a support vector machine, which is trained on a small set of hand-labeled silhouette exemplars. These exemplars are identified using a model-based preclassifier that utilizes calibrated images mapped by Google Earth to provide accurately surveyed scene geometry matched to visible image landmarks. Kalman filters track the vehicles to enable classification by majority voting over several consecutive frames. The system counts vehicles and separates them into four categories: car, van, bus, and motorcycle (including bicycles). Experiments with real-world data have been undertaken to evaluate system performance and vehicle detection rates of 96.45% and classification accuracy of 95.70% have been achieved on this data.The authors gratefully acknowledge the Royal Borough of Kingston for providing the video data. S.A. Velastin is grateful to funding received from the Universidad Carlos III de Madrid, the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement nº 600371, el Ministerio de Economía y Competitividad (COFUND2013-51509) and Banco Santander

Integración morfológica de la mandíbula de los ungulados nativos de América del Sur: un tributo a D’arcy Thompson en el centenario de “sobre el crecimiento y la forma”

South American native ungulates include several extinct lineages that evolved within the context of South American Cenozoic geographic isolation. By the late–early Miocene Santacrucian, the orders Notoungulata, Litopterna, and Astrapotheria were differentiated. Recent ecomorphological studies highlighted complex functional patterns between their habitat/diet and hypsodonty. In order to understand these relationships in an evolutionary context we used geometric morphometrics methods (27 3-D landmarks) to evaluate the morphological integration of two of the primary functional units of the mandible: the alveolar region and the ascending ramus. Principal component analyses (PCA) and two blocks Partial Least Squares analyses (PLS) were used to explore the patterns of variation and covariation between these two modules. The main variation in shape is related to the robusticity and curvature of the mandibular corpus, and the relative size of the angular and coronoid process. The PLS analyses show a very strong morphological integration within the Litopterna, but a pattern of modularity in the Notoungulata. There is a common pattern of covariation in Astrapotheria and Litopterna, which might be due to similar constraints. The different covariation patterns in notoungulates with respect to litopterns are in concordance with both the taxonomic and morphological diversity of the clades, particularly in the typotheres. The modularity present in notoungulates could have allowed specializations in each module of the mandible, related to crown height or muscle attachments, without a high morphological constrain. This could have resulted in their high morphological diversity, in contrast with the more conservative morphology present in litopterns.Los ungulados nativos de América del Sur incluyen varios linajes extintos que evolucionaron en el contexto de aislamiento geográfico del Cenozoico sudamericano. Durante el Santacrucense (Mioceno temprano), los órdenes Notoungulata, Litopterna y Astrapotheria ya estaban diferenciados. Los estudios ecomorfológicos recientes destacaron patrones funcionales complejos entre hábitat/dieta e hipsodoncia en estos grupos. Se analizan estas relaciones en un contexto evolutivo, utilizando métodos morfogeométricos (27 landmarks 3-D) para evaluar la integración morfológica de dos de las unidades funcionales principales de la mandíbula: región alveolar y rama ascendente. Para explorar los patrones de variación y covariación entre estos dos módulos, se utilizaron Análisis de componentes principales (PCA) y Análisis de mínimos cuadrados parciales de dos bloques (PLS). La variación principal de forma está relacionada con la robustez y la curvatura del cuerpo mandibular y el tamaño relativo de los procesos angular y coronoides. Los PLS muestran una integración morfológica muy fuerte en Litopterna y un patrón de modularidad en Notoungulata. Existe un patrón común de covariación en Astrapotheria y Litopterna que podría deberse a restricciones similares. Los diferentes patrones de covariación en notoungulados con respecto a los litopternos están en concordancia con la diversidad taxonómica y morfológica de los clados, particularmente en los tipoterios. La modularidad presente en Notoungulata habría permitido especializaciones en cada módulo de la mandíbula, relacionadas con la altura de la corona o las inserciones musculares, sin una alta restricción morfológica. Esto podría haber resultado en su alta diversidad morfológica, en contraste con la morfología más conservadora presente en Litopterna. Palabras clave. Notoungulata. Litopterna. Santacrucense. Morfometría GeométricaFacultad de Ciencias Naturales y Museo (FCNM