Robust Temporally Coherent Laplacian Protrusion Segmentation of 3D Articulated Bodies

In motion analysis and understanding it is important to be able to fit a suitable model or structure to the temporal series of observed data, in order to describe motion patterns in a compact way, and to discriminate between them. In an unsupervised context, i.e., no prior model of the moving object(s) is available, such a structure has to be learned from the data in a bottom-up fashion. In recent times, volumetric approaches in which the motion is captured from a number of cameras and a voxel-set representation of the body is built from the camera views, have gained ground due to attractive features such as inherent view-invariance and robustness to occlusions. Automatic, unsupervised segmentation of moving bodies along entire sequences, in a temporally-coherent and robust way, has the potential to provide a means of constructing a bottom-up model of the moving body, and track motion cues that may be later exploited for motion classification. Spectral methods such as locally linear embedding (LLE) can be useful in this context, as they preserve "protrusions", i.e., high-curvature regions of the 3D volume, of articulated shapes, while improving their separation in a lower dimensional space, making them in this way easier to cluster. In this paper we therefore propose a spectral approach to unsupervised and temporally-coherent body-protrusion segmentation along time sequences. Volumetric shapes are clustered in an embedding space, clusters are propagated in time to ensure coherence, and merged or split to accommodate changes in the body's topology. Experiments on both synthetic and real sequences of dense voxel-set data are shown. This supports the ability of the proposed method to cluster body-parts consistently over time in a totally unsupervised fashion, its robustness to sampling density and shape quality, and its potential for bottom-up model constructionComment: 31 pages, 26 figure

Capturing natural-colour 3D models of insects for species discovery

Collections of biological specimens are fundamental to scientific understanding and characterization of natural diversity. This paper presents a system for liberating useful information from physical collections by bringing specimens into the digital domain so they can be more readily shared, analyzed, annotated and compared. It focuses on insects and is strongly motivated by the desire to accelerate and augment current practices in insect taxonomy which predominantly use text, 2D diagrams and images to describe and characterize species. While these traditional kinds of descriptions are informative and useful, they cannot cover insect specimens "from all angles" and precious specimens are still exchanged between researchers and collections for this reason. Furthermore, insects can be complex in structure and pose many challenges to computer vision systems. We present a new prototype for a practical, cost-effective system of off-the-shelf components to acquire natural-colour 3D models of insects from around 3mm to 30mm in length. Colour images are captured from different angles and focal depths using a digital single lens reflex (DSLR) camera rig and two-axis turntable. These 2D images are processed into 3D reconstructions using software based on a visual hull algorithm. The resulting models are compact (around 10 megabytes), afford excellent optical resolution, and can be readily embedded into documents and web pages, as well as viewed on mobile devices. The system is portable, safe, relatively affordable, and complements the sort of volumetric data that can be acquired by computed tomography. This system provides a new way to augment the description and documentation of insect species holotypes, reducing the need to handle or ship specimens. It opens up new opportunities to collect data for research, education, art, entertainment, biodiversity assessment and biosecurity control.Comment: 24 pages, 17 figures, PLOS ONE journa

Stereoscopic motion analysis in densely packed clusters: 3D analysis of the shimmering behaviour in Giant honey bees

<p>Abstract</p> <p>Background</p> <p>The detailed interpretation of mass phenomena such as human escape panic or swarm behaviour in birds, fish and insects requires detailed analysis of the 3D movements of individual participants. Here, we describe the adaptation of a 3D stereoscopic imaging method to measure the positional coordinates of individual agents in densely packed clusters. The method was applied to study behavioural aspects of shimmering in Giant honeybees, a collective defence behaviour that deters predatory wasps by visual cues, whereby individual bees flip their abdomen upwards in a split second, producing Mexican wave-like patterns.</p> <p>Results</p> <p>Stereoscopic imaging provided non-invasive, automated, simultaneous, <it>in-situ </it>3D measurements of hundreds of bees on the nest surface regarding their thoracic position and orientation of the body length axis. <it>Segmentation </it>was the basis for the <it>stereo matching</it>, which defined correspondences of individual bees in pairs of stereo images. Stereo-matched "agent bees" were re-identified in subsequent frames by the <it>tracking </it>procedure and <it>triangulated </it>into real-world coordinates. These algorithms were required to calculate the three spatial motion components (dx: horizontal, dy: vertical and dz: towards and from the comb) of individual bees over time.</p> <p>Conclusions</p> <p>The method enables the assessment of the 3D positions of individual Giant honeybees, which is not possible with single-view cameras. The method can be applied to distinguish at the individual bee level active movements of the thoraces produced by abdominal flipping from passive motions generated by the moving bee curtain. The data provide evidence that the z-deflections of thoraces are potential cues for colony-intrinsic communication. The method helps to understand the phenomenon of collective decision-making through mechanoceptive synchronization and to associate shimmering with the principles of wave propagation. With further, minor modifications, the method could be used to study aspects of other mass phenomena that involve active and passive movements of individual agents in densely packed clusters.</p

Stereo vision without the scene-smoothness assumption: the homography-based approach.

by Andrew L. Arengo.Thesis (M.Phil.)--Chinese University of Hong Kong, 1998.Includes bibliographical references (leaves 65-66).Abstract also in Chinese.Acknowledgments --- p.iiList Of Figures --- p.vAbstract --- p.viiChapter 1 --- Introduction --- p.1Chapter 1.1 --- Motivation and Objective --- p.2Chapter 1.2 --- Approach of This Thesis and Contributions --- p.3Chapter 1.3 --- Organization of This Thesis --- p.4Chapter 2 --- Previous Work --- p.6Chapter 2.1 --- Using Grouped Features --- p.6Chapter 2.2 --- Applying Additional Heuristics --- p.7Chapter 2.3 --- Homography and Related Works --- p.9Chapter 3 --- Theory and Problem Formulation --- p.10Chapter 3.1 --- Overview of the Problems --- p.10Chapter 3.1.1 --- Preprocessing --- p.10Chapter 3.1.2 --- Establishing Correspondences --- p.11Chapter 3.1.3 --- Recovering 3D Depth --- p.14Chapter 3.2 --- Solving the Correspondence Problem --- p.15Chapter 3.2.1 --- Epipolar Constraint --- p.15Chapter 3.2.2 --- Surface-Continuity and Feature-Ordering Heuristics --- p.16Chapter 3.2.3 --- Using the Concept of Homography --- p.18Chapter 3.3 --- Concept of Homography --- p.20Chapter 3.3.1 --- Barycentric Coordinate System --- p.20Chapter 3.3.2 --- Image to Image Mapping of the Same Plane --- p.22Chapter 3.4 --- Problem Formulation --- p.23Chapter 3.4.1 --- Preliminaries --- p.23Chapter 3.4.2 --- Case of Single Planar Surface --- p.24Chapter 3.4.3 --- Case of Multiple Planar Surfaces --- p.28Chapter 3.5 --- Subspace Clustering --- p.28Chapter 3.6 --- Overview of the Approach --- p.30Chapter 4 --- Experimental Results --- p.33Chapter 4.1 --- Synthetic Images --- p.33Chapter 4.2 --- Aerial Images --- p.36Chapter 4.2.1 --- T-shape building --- p.38Chapter 4.2.2 --- Rectangular Building --- p.39Chapter 4.2.3 --- 3-layers Building --- p.40Chapter 4.2.4 --- Pentagon --- p.44Chapter 4.3 --- Indoor Scenes --- p.52Chapter 4.3.1 --- Stereo Motion Pair --- p.53Chapter 4.3.2 --- Hallway Scene --- p.56Chapter 5 --- Summary and Conclusions --- p.6

168 million years old "marine lice" and the evolution of parasitism within isopods

BACKGROUND: Isopods (woodlice, slaters and their relatives) are common crustaceans and abundant in numerous habitats. They employ a variety of lifestyles including free-living scavengers and predators but also obligate parasites. This modern-day variability of lifestyles is not reflected in isopod fossils so far, mostly as the life habits of many fossil isopods are still unclear. A rather common group of fossil isopods is Urda (190-100 million years). Although some of the specimens of different species of Urda are considered well preserved, crucial characters for the interpretation of their lifestyle (and also of their phylogenetic position), have so far not been accessible. RESULTS: Using up-to-date imaging methods, we here present morphological details of the mouthparts and the thoracopods of 168 million years old specimens of Urda rostrata. Mouthparts are of a sucking-piercing-type morphology, similar to the mouthparts of representatives of ectoparasitic isopods in groups such as Aegidae or Cymothoidae. The thoracopods bear strong, curved dactyli most likely for attaching to a host. Therefore, mouthpart and thoracopod morphology indicate a parasitic lifestyle of Urda rostrata. Based on morphological details, Urda seems deeply nested within the parasitic isopods of the group Cymothoida. CONCLUSIONS: Similarities to Aegidae and Cymothoidae are interpreted as ancestral characters; Urda is more closely related to Gnathiidae, which is therefore also interpreted as an ingroup of Cymothoida. With this position Urda provides crucial information for our understanding of the evolution of parasitism within isopods. Finally, the specimens reported herein represent the oldest parasitic isopods known to date

Activity profiling for minimally invasive surgery

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