Evaluating and Grading Students in Large-Scale Image Processing Courses.

In undergraduate practical courses, it is common to work with groups of 100 or more students. These large-scale courses bring their own challenges. For example, course problems are too small and lack "the big picture"; grading becomes burdensome and repetitive for the teaching staff; and it is difficult to detect cheating. Based on their experience with a traditional large-scale practical course in image processing, the authors developed a novel course approach to teaching "Introduction to Digital Image Processing" (or EDBV, from the German course title Einführung in die Digitale Bild-Verarbeitung) for all undergraduate students of media informatics and visual computing and medical informatics at the TU Wien.

Comparison of three-dimensional surface-imaging systems.

BACKGROUND: In recent decades, three-dimensional (3D) surface-imaging technologies have gained popularity worldwide, but because most published articles that mention them are technical, clinicians often have difficulties gaining a proper understanding of them. This article aims to provide the reader with relevant information on 3D surface-imaging systems. In it, we compare the most recent technologies to reveal their differences. METHODS: We have accessed five international companies with the latest technologies in 3D surface-imaging systems: 3dMD, Axisthree, Canfield, Crisalix and Dimensional Imaging (Di3D; in alphabetical order). We evaluated their technical equipment, independent validation studies and corporate backgrounds. RESULTS: The fastest capturing devices are the 3dMD and Di3D systems, capable of capturing images within 1.5 and 1 ms, respectively. All companies provide software for tissue modifications. Additionally, 3dMD, Canfield and Di3D can fuse computed tomography (CT)/cone-beam computed tomography (CBCT) images into their 3D surface-imaging data. 3dMD and Di3D provide 4D capture systems, which allow capturing the movement of a 3D surface over time. Crisalix greatly differs from the other four systems as it is purely web based and realised via cloud computing. CONCLUSION: 3D surface-imaging systems are becoming important in today's plastic surgical set-ups, taking surgeons to a new level of communication with patients, surgical planning and outcome evaluation. Technologies used in 3D surface-imaging systems and their intended field of application vary within the companies evaluated. Potential users should define their requirements and assignment of 3D surface-imaging systems in their clinical as research environment before making the final decision for purchase.

On the search of optimal reconstruction resolution.

In this paper we present a novel algorithm to optimize the reconstruction from non-uniform point sets. We introduce a statistically-derived topology-controller for selecting the reconstruction resolution of a given non-uniform point set. Deriving information from homology-based statistics, our topology-controller ensures a stable and sound basis for the analysis process. By analyzing our topology-controller, we select an optimal reconstruction resolution which ensures both low reconstruction errors and a topological stability of the underlying signal. Our approach offers a valuable method for the evaluation of the reconstruction process without the need of visual inspection of the reconstructed datasets. By means of qualitative results we show how our proposed topology statistics provides complementary information in the enhancement of existing reconstruction pipelines in visualization.

Hierarchical spatio-temporal extraction of models for moving rigid parts.

This paper presents a method to extract a part-based model of an observed scene from a video sequence. Independent motion is a strong cue that two points belong to different "rigid" entities. Conversely, things that move together throughout the whole video belong together and define a "rigid" object or part. Successfully tracked features indicate trajectories of salient points in the scene. A triangulated graph connects the salient points and encodes their local neighborhood in the first frame. The length variation of the triangle edges is used to label them as relevant (on an object) or separating (connecting different objects). A following grouping process uses the motion of the triangles marked as relevant as a cue to identify the "rigid" parts of the foreground or the background. The choice of the motion-based grouping criterion depends on the type of motion: in the image plane or out of the image plane. The result is a hierarchical description (graph pyramid) of the scene, where each vertex in the top level of the pyramid represents a "rigid" part of the foreground or the background, and encloses to the salient features used to describe it. Promising experimental results show the potential of the approach.

Multi-scale 2D tracking of articulated objects using hierarchical spring systems.

This paper presents a flexible framework to build a target-specific, part-based representation for arbitrary articulated or rigid objects. The aim is to successfully track the target object in 2D, through multiple scales and occlusions. This is realized by employing a hierarchical, iterative optimization process on the proposed representation of structure and appearance. Therefore, each rigid part of an object is described by a hierarchical spring system represented by an attributed graph pyramid. Hierarchical spring systems encode the spatial relationships of the features (attributes of the graph pyramid) describing the parts and enforce them by spring-like behavior during tracking. Articulation points connecting the parts of the object allow to transfer position information from reliable to ambiguous parts. Tracking is done in an iterative process by combining the hypotheses of simple trackers with the hypotheses extracted from the hierarchical spring systems.

New approach to the perception of 3D shape based on veridicality, complexity, symmetry and volume.

This paper reviews recent progress towards understanding 3D shape perception made possible by appreciating the significant role that veridicality and complexity play in the natural visual environment. The ability to see objects as they really are "out there" is derived from the complexity inherent in the 3D object's shape. The importance of both veridicality and complexity was ignored in most prior research. Appreciating their importance made it possible to devise a computational model that recovers the 3D shape of an object from only one of its 2D images. This model uses a simplicity principle consisting of only four a priori constraints representing properties of 3D shapes, primarily their symmetry and volume. The model recovers 3D shapes from a single 2D image as well, and sometimes even better, than a human being. In the rare recoveries in which errors are observed, the errors made by the model and human subjects are very similar. The model makes no use of depth, surfaces or learning. Recent elaborations of this model include: (i) the recovery of the shapes of natural objects, including human and animal bodies with limbs in varying positions (ii) providing the model with two input images that allowed it to achieve virtually perfect shape constancy from almost all viewing directions. The review concludes with a comparison of some of the highlights of our novel, successful approach to the recovery of 3D shape from a 2D image with prior, less successful approaches.