1,720,962 research outputs found
Estimation of contact regions between hands and objects during human multi-digit grasping
To grasp an object successfully, we must select appropriate contact regions for our hands on the surface of the object. However, identifying such regions is challenging. This paper describes a workflow to estimate the contact regions from marker-based tracking data. Participants grasp real objects, while we track the 3D position of both the objects and the hand, including the fingers' joints. We first determine the joint Euler angles from a selection of tracked markers positioned on the back of the hand. Then, we use state-of-the-art hand mesh reconstruction algorithms to generate a mesh model of the participant's hand in the current pose and the 3D position. Using objects that were either 3D printed or 3D scanned-and are, thus, available as both real objects and mesh data-allows the hand and object meshes to be co-registered. In turn, this allows the estimation of approximate contact regions by calculating the intersections between the hand mesh and the co-registered 3D object mesh. The method may be used to estimate where and how humans grasp objects under a variety of conditions. Therefore, the method could be of interest to researchers studying visual and haptic perception, motor control, human-computer interaction in virtual and augmented reality, and robotics.</p
An image-computable model of human visual shape similarity
Shape is a defining feature of objects, and human observers can effortlessly compare shapes to determine how similar they are. Yet, to date, no image-computable model can predict how visually similar or different shapes appear. Such a model would be an invaluable tool for neuroscientists and could provide insights into computations underlying human shape perception. To address this need, we developed a model (‘ShapeComp’), based on over 100 shape features (e.g., area, compactness, Fourier descriptors). When trained to capture the variance in a database of >25,000 animal silhouettes, ShapeComp accurately predicts human shape similarity judgments between pairs of shapes without fitting any parameters to human data. To test the model, we created carefully selected arrays of complex novel shapes using a Generative Adversarial Network trained on the animal silhouettes, which we presented to observers in a wide range of tasks. Our findings show that incorporating multiple ShapeComp dimensions facilitates the prediction of human shape similarity across a small number of shapes, and also captures much of the variance in the multiple arrangements of many shapes. ShapeComp outperforms both conventional pixel-based metrics and state-of-the-art convolutional neural networks, and can also be used to generate perceptually uniform stimulus sets, making it a powerful tool for investigating shape and object representations in the human brain.</p
Mental object rotation based on two-dimensional visual representations
The discovery of mental rotation was one of the most significant landmarks in experimental psychology, leading to the ongoing assumption that to visually compare objects from different three-dimensional viewpoints, we use explicit internal simulations of object rotations, to ‘mentally adjust’ one object until it matches the other1. These rotations are thought to be performed on three-dimensional representations of the object, by literal analogy to physical rotations. In particular, it is thought that an imagined object is continuously adjusted at a constant three-dimensional angular rotation rate from its initial orientation to the final orientation through all intervening viewpoints2. While qualitative theories have tried to account for this phenomenon3, to date there has been no explicit, image-computable model of the underlying processes. As a result, there is no quantitative account of why some object viewpoints appear more similar to one another than others when the three-dimensional angular difference between them is the same4,5. We reasoned that the specific pattern of non-uniformities in the perception of viewpoints can reveal the visual computations underlying mental rotation. We therefore compared human viewpoint perception with a model based on the kind of two-dimensional ‘optical flow’ computations that are thought to underlie motion perception in biological vision6, finding that the model reproduces the specific errors that participants make. This suggests that mental rotation involves simulating the two-dimensional retinal image change that would occur when rotating objects. When we compare objects, we do not do so in a distal three-dimensional representation as previously assumed, but by measuring how much the proximal stimulus would change if we watched the object rotate, capturing perspectival appearance changes7.</p
Does precision grip research extend to unconstrained, multidigit grasping?
Most daily tasks require using our hands. Whether taking a sip from a glass or throwing a ball, we effortlessly select appropriate grasps. Yet, despite many possible hand configurations, most grasping research has focused on the finger-and-thumb “precision grip.” We thus questioned whether findings on precision grip—such as sensitivity to object mass and material configuration—hold under unconstrained grasping conditions. To test this, we compared how participants grasped three-dimensional (3-D) objects made of brass and wood, with both precision grip and unconstrained grasps. When unconstrained, participants rarely selected precision grips, favoring multidigit grasps. Nevertheless, in both conditions, participants shifted their grasps toward the objects’ center of mass and, when grasp factors conflicted, the variability in their selections increased, indicating greater uncertainty about the optimal strategy. Furthermore, despite favoring multidigit grasps, participants consistently placed the thumb and index finger on the same positions on the objects, suggesting that in multidigit grasps, the additional fingers primarily provided support. Our findings thus reveal that object material affects unconstrained grasping similarly to precision grip and imply that previous precision grip research may extend to unconstrained, multidigit conditions
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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