2D shape classification and retrieval

We present a novel correspondence-based technique for efficient shape classification and retrieval. Shape boundaries are described by a set of (ad hoc) equally spaced points – avoiding the need to extract “landmark points”. By formulating the correspondence problem in terms of a simple generative model, we are able to efficiently compute matches that incorporate scale, translation, rotation and reflection invariance. A hierarchical scheme with likelihood cut-off provides additional speed-up. In contrast to many shape descriptors, the concept of a mean (prototype) shape follows naturally in this setting. This enables model based classification, greatly reducing the cost of the testing phase. Equal spacing of points can be defined in terms of either perimeter distance or radial angle. It is shown that combining the two leads to improved classification/retrieval performance.

A physiological measure of shifting connections in the Rana pipiens retinotectal system

The retinotectal connections of developing Rana tadpoles and froglets have been studied using light-pipe techniques to directly assay the pattern of the projection from the retina to the tectum. The projection site of the retina surrounding the optic nerve head was determined at two different stages of development (late larval and metamorphic frog) on the same animal. Small electrolytic marker lesions were used to mark the tectal sites to which the optic nerve head projected at these two times. Comparison of the positions of the two lesions gives a direct measure of the shift in the projection during the interlesion time interval of one week. The results indicate a shift in the projection of 275 µm week–1 in late larval life. Previous work in Xenopus using the light-pipe techniques indicated a qualitatively similar shift during equivalent stages of development, but significantly smaller in magnitude. In the present study, topographic postsynaptic units could be recorded at all stages investigated, indicating functional synapses between the optic nerve fibres and the tectum. Thus, these studies offer evidence of a significant shift in the functional connection pattern of the amphibian retinotectal map during development, in agreement with the recent anatomical data from other laboratories on the Rana and goldfish visual system

Persistent Evidence of Local Image Properties in Generic ConvNets

Supervised training of a convolutional network for object classification should make explicit any information related to the class of objects and disregard any auxiliary information associated with the capture of the image or the variation within the object class. Does this happen in practice? Although this seems to pertain to the very final layers in the network, if we look at earlier layers we find that this is not the case. Surprisingly, strong spatial information is implicit. This paper addresses this, in particular, exploiting the image representation at the first fully connected layer, i.e. the global image descriptor which has been recently shown to be most effective in a range of visual recognition tasks. We empirically demonstrate evidences for the finding in the contexts of four different tasks: 2d landmark detection, 2d object keypoints prediction, estimation of the RGB values of input image, and recovery of semantic label of each pixel. We base our investigation on a simple framework with ridge rigression commonly across these tasks, and show results which all support our insight. Such spatial information can be used for computing correspondence of landmarks to a good accuracy, but should potentially be useful for improving the training of the convolutional nets for classification purposes

Epiplastral and geographic variation in Echmatemys, a geoemydid turtle from the Eocene of North America: A multi-tiered analysis of epiplastral shape complexity

Numerous geoemydid turtle fossils from the extinct genus Echmatemys have been recovered from the middle Eocene Uinta Formation, Uinta Basin, Utah over the past several decades. Here, we tested whether co-occurring Uintan species Echmatemys callopyge and E. uintensis can be reliably differentiated based on epiplastral morphology, and whether their geospatial distributions overlapped significantly. The geographic spatial and stratigraphic distributions of Uinta Basin E. callopyge and E. uintensis specimens were compared using ArcGIS and analysis of variance (ANOVA). The analysis revealed overlapping geographic distributions of these two species, and no significant differences in stratigraphic dispersal. This finding of extensive geospatial overlap between the two Uintan Echmatemys species highlights the need for accurate taxonomic identification, such as the gular scale morphology validated here. In addition, we sought to address a methodological question regarding the relative efficacy of data complexity in this context. Using epiplastra from three additional Eocene species of Echmatemys, we employed hierarchical analyses of increasing data complexity, from standard linear dimensions to 2D geometric morphometrics to 3D laser scans, to determine the degree to which data complexity contributes to taxonomic assessments within this genus. Uintan species E. callopyge and E. uintensis were found to differ significantly in epiplastral shape as captured by all three categories of data. These findings verify that these two co-occurring species can be differentiated consistently using the shape of the gular scale, and that the use of geometric morphometrics can improve identification of fragmentary specimens. Among the non-Uintan species, dorsal and ventral 2D landmark data reliably differentiated among species, but the linear dimensions were less useful

Phenotype and animal domestication : A study of dental variation between domestic, wild, captive, hybrid and insular Sus scrofa

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Acknowledgements We thank the institutions and individuals that provided access to collections, especially the curators of the Museum für Naturkunde, Berlin; Zoologische Staatssammlung, München; Muséum National d’Histoire Naturelle, Paris; Muséum d’Histoire Naturelle, Genève; National Museum of Natural History, Washington; The Field Museum, Chicago and The American Museum of Natural History, New-York. We also thank Jean-Denis Vigne, Nelly Gidaszewski, Vincent Debat and Mathieu Joron for fruitful discussions. This work was supported by a research grant from the Natural Environment Research Council, UK (grant number NE/F003382/1).Peer reviewedPublisher PD

Accuracy of generic mesh conformation: the future of facial morphological analysis

Three-dimensional (3D) analysis of the face is required for the assessment of changes following surgery, to monitor the progress of pathological conditions and for the evaluation of facial growth. Sophisticated methods have been applied for the evaluation of facial morphology, the most common being dense surface correspondence. The method depends on the application of a mathematical facial mask known as the generic facial mesh for the evaluation of the characteristics of facial morphology. This study evaluated the accuracy of the conformation of generic mesh to the underlying facial morphology. The study was conducted on 10 non-patient volunteers. Thirty-four 2-mm-diameter self-adhesive, non-reflective markers were placed on each face. These were readily identifiable on the captured 3D facial image, which was captured by Di3D stereophotogrammetry. The markers helped in minimising digitisation errors during the conformation process. For each case, the face was captured six times: at rest and at the maximum movements of four facial expressions. The 3D facial image of each facial expression was analysed. Euclidean distances between the 19 corresponding landmarks on the conformed mesh and on the original 3D facial model provided a measure of the accuracy of the conformation process. For all facial expressions and all corresponding landmarks, these distances were between 0.7 and 1.7 mm. The absolute mean distances ranged from 0.73 to 1.74 mm. The mean absolute error of the conformation process was 1.13 ± 0.26 mm. The conformation of the generic facial mesh is accurate enough for clinical trial proved to be accurate enough for the analysis of the captured 3D facial images