A new view on grasping.

In this study, we mainly investigated the visual selectivity of hand-manipulation-related neurons in the anterior intraparietal area (area AIP) while the animal was grasping or fixating on three-dimensional (3D) objects of different geometric shapes, sizes, and orientations. We studied the activity of 132 task-related neurons during the hand-manipulation tasks in the light and in the dark, as well as during object fixation. Seventy-seven percent (101/132) of the hand-manipulation-related neurons were visually responsive, showing either lesser activity during manipulation in the dark than during that in the light (visual-motor neurons) or no activation in the dark (visual-dominant neurons). Of these visually responsive neurons, more than half (n = 66) responded during the object-fixation task (object-type). Among these, 55 were tested for their shape selectivity during the object-fixation task, and many (n = 25) were highly selective, preferring one particular shape of the six different shapes presented (ring, cube, cylinder, cone, sphere, and square plate). For 28 moderately selective object-type neurons, we performed multidimensional scaling (MDS) to examine how the neurons encode the similarity of objects. The results suggest that some moderately selective neurons responded preferentially to common geometric features shared by similar objects (flat, round, elongated, etc.). Moderately selective nonobject-type visually responsive neurons, which did not respond during object fixation, were found by MDS to be more closely related to the handgrip than to the object shape. We found a similar selectivity for handgrip in motor-dominant neurons that did not show any visual response. With regard to the size of the objects, 16 of 26 object-type neurons tested were selective for both size and shape, whereas 9 object-type neurons were selective for shape but not for size. Seven of 12 nonobject-type and all (8/8) of the motor-dominant neurons examined were selective for size, and almost all of them were also selective for objects. Many hand-manipulation-related neurons that preferred the plate and/or ring were selective for the orientation of the objects (17/20). These results suggest that the visual responses of object-type neurons represent the shape, size, and/or orientation of 3D objects, whereas those of the nonobject-type neurons probably represent the shape of the handgrip, grip size, or hand-orientation. The activity of motor-dominant neurons was also, in part, likely to represent these parameters of hand movement. This suggests that the dorsal visual pathway is concerned with the aspect of form, orientation, and/or size perception that is relevant for the visual control of movements.

The development of prehension was studied in babies aged between 6 and 20 months in a partial replication of the classic study by Halverson (1931). In our study the objects to be grasped were spheres and cubes carefully graded to allow comparisons of grips with object shape and size controlled. The trend noted by Halverson, for power grips to decrease and precision grips to increase, was replicated so that by the second year precision grasping is the dominant mode of prehension. However, the transition to precision grasping appears to occur by selection from a developmentally prior mixture of power and precision grips. In comparing spheres and cubes object size was the most important factor influencing grip selection but object shape also had a lesser influence. Object size may have acted as a scaling factor for grip selection. The findings are discussed in relation to a selectionist approach to the development of prehension.

For stereoscopic photography or telepresence, orthostereoscopy occurs when the perceived size, shape, and relative position of objects in the three-dimensional scene being viewed match those of the physical objects in front of the camera. In virtual reality, the simulated scene has no physical counterpart, so orthostereoscopy must be defined in this case as constancy, as the head moves around, of the perceived size, shape, and relative positions of the simulated objects. Achieving this constancy requires that the computational model used to generate the graphics matches the physical geometry of the head-mounted display being used. This geometry includes the optics used to image the displays and the placement of the displays with respect to the eyes. The model may fail to match the geometry because model parameters are difficult to measure accurately, or because the model itself is in error. Two common modeling errors are ignoring the distortion caused by the optics and ignoring the variation in interpupillary distance across different users. A computational model for the geometry of a head-mounted display is presented, and the parameters of this model for the VPL EyePhone are calculated.

This paper proposes a method for estimating 3D information, such as shape, orientation, size, and position of objects in a monocular image, and reproduce scenes in 3D point clouds using Convolutional Neural Network (CNN). This study proposes a network that combines depth estimation, object detection, and point cloud estimation to estimate 3D information of objects. The proposed network requires networks for object detection and segmentation, and a point cloud estimation for object shape estimation. The point cloud estimation network is robust to the reproduction of the object's surface and can deal with unknown objects through a semantic understanding of the object’s shape. In addition to these networks, we combine a depth estimation network for estimating the depth of the entire scene and the distance between the camera and object. In this paper, we consider the point cloud estimation network. We estimate the point clouds for real objects in the images of the dataset and evaluate the output point clouds.

Visual illusions occur around us all the time, which present in nature and appear when you least expect it. It is well known that visual illusions can have a dramatic effect upon our visual perception of an object 's size and position. However, whether visual illusions have a similar influence on visual guided action or not, it remains the subject of much debate. The purpose of this study is to explore whether the visual information used to identify and categorize an object would be similar to the visual information used to plan and control visually guided movements directed toward that object. The outcome of this study will be helpful for designers to understand our visual information system and apply that knowledge to the design practice. In order to achieve the purpose of this study mentioned above, three visual illusions as the experiment's apparatus are applied to examine the relative effect of visual illusions on both the visual perceived center of an object and the position of a grasp on that object when a balanced lift is required. The results of the experiment show that (1) Illusions influence both the perceived and the grasped estimates of the center position, but the grasp center is more veridical; (2) Judd-illusion, one of the three visual illusions, has a bigger degree of effect than two other illusions on both the perceived and the grasped estimates of the center position; (3) By providing the participants with a mean to guide their visual perception of these illusions, the errors from the estimation of the center position can be significantly reduced.

Optimising haptic sensitivity in visual-haptic interfaces can have important benefits, particularly in situations where visual information is relatively unreliable (for example in surgical devices, where there is often a lack of normal visual depth cues). Many haptic devices alter the normal relationship between object size and hand opening, and so might be expected to alter haptic sensitivity. To determine how to optimise haptic sensitivity in such situations, we measured haptic size sensitivity as a function of object size (i) during normal grasping, and (ii) using pliers-like tools that changed the gain between hand opening and object size. Haptic stimuli were created using force-feedback robots, and we measured discrimination thresholds using a two-interval forced-choice task. We first showed that when participants directly grasped objects with their hands haptic size sensitivity did not follow Weber’s law, but instead varied non-monotonically with object size/hand opening; thresholds were lowest for object sizes around 45 mm and increased non-linearly for larger and smaller objects. Second, when using the pliers, sensitivity in units of hand opening was unchanged from normal grasping. Thus, thresholds in units of object size were simply the product of the non-monotonic haptic size sensitivity function, above, and the tool gain. Taken together, these results show that there is a unique tool gain that maximises haptic sensitivity to each object size. Our results show how the ‘tool gain’ of haptic devices should be altered to optimise sensitivity to the range of object sizes in a particular scene.

Lines and surfaces are boundary elements of objects and buildings: it is very important to give the students a mathematical approach to them. Elena Marchetti and Luisa Rossi Costa present linear algebra (by vectors and matrices) as an elegant and synthetic method, not only for the description but also for the virtual reconstruction of shapes.The aim of our activity is to facilitate—and, at the same time, to develop—the comprehension of crucial mathematical tools involved in the realization of forms and shapes in arts, architecture and industrial design and in computer graphics. Another important aspect of linear algebra to be pointed out to the students is its application in graphics software packages, which work with transformations that change the position, orientation and size of objects in a drawing

A Real-World Size Organization of Object Responses in Occipitotemporal Cortex

The purpose of our study was to investigate how image magnification and distortion in dental panoramic radiography are influenced by object size and position for a small round object such as a ball bearing used for calibration. Two ball bearings (2.5 mm and 6 mm in diameter) were placed at approximately the same position between the teeth of a plastic skull and radiographed 21 times. The skull was replaced each time. Their images were measured by software using edge detection and ellipse-fitting algorithms. Using a standard definition of magnification, equations were derived to enable an object's magnification to be determined from its position and vice versa knowing the diameter and machine parameters. The average magnification of the 2.5 mm ball bearing was 1.292 (0.0445) horizontally and 1.257 (0.0067) vertically with a mean ratio of 1.028 (0.0322); standard deviations are in parentheses. The figures for the 6 mm ball bearing were 1.286 (0.0068), 1.255 (0.0018) and 1.025 (0.0061), respectively. Derived positions of each ball bearing from magnification were more consistent horizontally than vertically. There was less variation in either direction for the 6 mm ball bearing than the 2.5 mm one. Automatic measurement of image size resulted in less variation in vertical magnification values than horizontal. There are only certain positions in the focal trough that achieve zero distortion. Object location can be determined from its diameter, measured magnification and machine parameters. The 6 mm diameter ball bearing is preferable to the 2.5 mm one for more reliable magnification measurement and position determination.

As an important part of the nervous system, the human visual system can provide visual perception for humans. The research on it is of great significance to improve our understanding of biological vision and the human brain. Orientation detection, in which visual cortex neurons respond only to linear stimuli in specific orientations, is an important driving force in computer vision and biological vision. However, the principle of orientation detection is still unknown. This paper proposes an orientation detection mechanism based on dendrite calculation of local orientation detection neurons. We hypothesized the existence of orientation detection neurons that only respond to specific orientations and designed eight neurons that can detect local orientation information. These neurons interact with each other based on the nonlinearity of dendrite generation. Then, local orientation detection neurons are used to extract local orientation information, and global orientation information is deduced from local orientation information. The effectiveness of the mechanism is verified by computer simulation, which shows that the machine can perform orientation detection well in all experiments, regardless of the size, shape, and position of objects. This is consistent with most known physiological experiments.

abstractBerkeley thinks that we only see the size, shape, location, and orientation of objects in virtue of the correlation between sight and touch. Shadows have all of these spatial properties and yet are intangible. In Seeing Dark Things (2008), Roy Sorensen argues that shadows provide a counterexample to Berkeley's theory of vision and, consequently, to his idealism. This paper shows that Berkeley can accept both that shadows are intangible and that they have spatial properties.

Speckle backscatter form actively illuminated satellites contains information on object size, shape and orientation and on the optical properties of the object materials. This speckle information is useful for object discrimination and classification tasks. In particular, the polarization properties of these materials may provide unique signatures that enhance the discrimination between certain objects. This simulation investigation explores the use of polarization information in speckle backscatter to form useful polarization signatures. The simulation uses detailed polarization renderings of objects and coherent field propagation techniques to form pupil plane speckle polarization components fields characteristic of the object materials' polarization properties. The fields are then converted to four speckle intensity fields using a four- channel polarimeter model and are spatially resolved with an array of detectors. Polarization signature information is obtained from Stokes parameters and Mueller matrices formed from these speckle measurements. The object polarization signatures considered include depolarization, diattenuation and retardance. These parameters are calculated for several object models to illustrate their possible use in object discrimination and to investigate their sensitivity to perturbing effects. The perturbing effects of detection noise, passive unpolarized background and atmospheric turbulence are considered. Spatial and temporal averaging of the Stokes parameter fields is shown to reduce the effect of these errors on the polarization parameters yielding improved signature measurements. Estimation and removal of unpolarized components from the speckle measurements is also shown to improve signature accuracy.

This article presents an analysis into the accuracy and problems of freehand grasping in exocentric Mixed Reality (MR). We report on two experiments (1710 grasps) which quantify the influence different virtual object shape, size and position has on the most common physical grasp, a medium wrap. We propose two methods for grasp measurement, namely, the Grasp Aperture (GAp) and Grasp Displacement (GDisp). Controlled laboratory conditions are used where 30 right-handed participants attempt to recreate a medium wrap grasp. We present a comprehensive statistical analysis of the results giving pairwise comparisons of all conditions under test. The results illustrate that user Grasp Aperture varies less than expected in comparison to the variation of virtual object size, with common aperture sizes found. Regarding the position of the virtual object, depth estimation is often mismatched due to under judgement of the z position and x, y displacement has common patterns. Results from this work can be applied to aid in the development of freehand grasping and considered as the first study into accuracy of freehand grasping in MR, provide a starting point for future interaction design.

The web search strategy by the photograph and the voice are paid to attention today. And, the demand of the search strategy by the memory and the thinking will rise in the future. However, the device and the input method for them are discussed still hardly. In this study, three basic survey researches were conducted to consider an intuitive operation. In results about the images that people want to transmit, such as the size or shape of object, the image of character and the thinking were enumerated. And, it was suggested that to transmit the size of object a gesture was more intuitive, for example. Also, it was suggested that to transmit the thinking the linguistic expression was more intuitive. For system production or device production, it is preferable to consider these results.

Passive Millimeter Wave Images (PMMWI) can be used to detect and localize objects concealed under clothing. Unfortunately, the quality of the acquired images and the unknown position, shape, and size of the hidden objects render difficult this task. In this paper we propose a method that combines image processing and statistical machine learning techniques to solve this localization/detection problem. The proposed approach is used on an image database containing a broad variety of sizes, types, and localizations of hidden objects. Experiments are presented in terms of the true positive and false positive detection rates. Due to its high performance and low computational cost, the proposed method can be used in real time applications.