Synthetic Objects Research Articles

Interacting in 3D Space: Comparison of a 3D Two-handed Interface to a Keyboard-and-mouse Interface for Medical 3D Image Manipulation

Interacting with computer-generated 3-dimensional (3D) data can pose challenges in the control of 3D objects and navigation in 3D space. The traditional mouse-driven interfaces are limited to controlling two degrees of freedom (DOF) at a time. The current research examines the efficacy of a two-handed interface (THI), “iMedic,” that uses two 6-DOF controllers that afford a more direct style of manipulation of 3D medical imagery. The iMedic interface employs a 3D “multi-touch” type of interaction for manipulation of objects, and self-navigation in space. Medical 3D images of human anatomy from computer tomography (CT) scans were used as a testbed in comparing the two interface: the THI, and a traditional keyboard-and-mouse interface (KMI) commonly used in medical imaging contexts. Novice system users with medical background used each system to carry out navigation, visual search, and measurement tasks with abstract synthetic and realistic anatomical objects. Results indicate that for novice users, there was no clear advantage to either interface in subjective or objective measures. However, a case study of an experienced user showed clear advantages in all tasks using the THI. Reasons for the findings are examined, and interface design implications are discussed.

Interacting in 3D Space: Comparison of a 3D Two-handed Interface to a Keyboard-and-mouse Interface for Medical 3D Image Manipulation

Interacting with computer-generated 3-dimensional (3D) data can pose challenges in the control of 3D objects and navigation in 3D space. The traditional mouse-driven interfaces are limited to controlling two degrees of freedom (DOF) at a time. The current research examines the efficacy of a two-handed interface (THI), “iMedic,” that uses two 6-DOF controllers that afford a more direct style of manipulation of 3D medical imagery. The iMedic interface employs a 3D “multi-touch” type of interaction for manipulation of objects, and self-navigation in space. Medical 3D images of human anatomy from computer tomography (CT) scans were used as a testbed in comparing the two interface: the THI, and a traditional keyboard-and-mouse interface (KMI) commonly used in medical imaging contexts. Novice system users with medical background used each system to carry out navigation, visual search, and measurement tasks with abstract synthetic and realistic anatomical objects. Results indicate that for novice users, there was no clear advantage to either interface in subjective or objective measures. However, a case study of an experienced user showed clear advantages in all tasks using the THI. Reasons for the findings are examined, and interface design implications are discussed.

SecondSkin: An interactive method for appearance transfer

SecondSkin estimates an appearance model for an object visible in a video sequence, without the need for complex interaction or any calibration apparatus. This model can then be transferred to other objects, allowing a non-expert user to insert a synthetic object into a real video sequence so that its appearance matches that of an existing object, and changes appropriately throughout the sequence. As the method does not require any prior knowledge about the scene, the lighting conditions, or the camera, it is applicable to video which was not captured with this purpose in mind. However, this lack of prior knowledge precludes the recovery of separate lighting and surface reflectance information. The SecondSkin appearance model therefore combines these factors. The appearance model does require a dominant light-source direction, which we estimate via a novel process involving a small amount of user interaction. The resulting model estimate provides exactly the information required to transfer the appearance of the original object to new geometry composited into the same video sequence.

MRT letter: Recovering weak‐textured surfaces using image focus

In nature, objects have partially weak texture and their shape reconstruction using focus based passive methods like shape from focus (SFF), is difficult. This article presents a new SFF algorithm which can compute precise depth of dense as well as weak textured objects. Segmentation is applied to discard wrong depth estimate and then later interpolating them from accurate depth values of their neighbors. The performance of the proposed method is tested, using different image sequences of synthetic and real objects, with varying textures.

A FRAMEWORK FOR ACTIVELY SELECTING VIEWPOINTS IN OBJECT RECOGNITION

Object recognition problems in computer vision are often based on single image data processing. In various applications this processing can be extended to a complete sequence of images, usually received passively. In contrast, we propose a method for active object recognition, where a camera is selectively moved around a considered object. Doing so, we aim at reliable classification results with a clearly reduced amount of necessary views by optimizing the camera movement for the access of new viewpoints (viewpoint selection). Therefore, the optimization criterion is the gain of class discriminative information when observing the appropriate next image. We show how to apply an unsupervised reinforcement learning algorithm to that problem. Specifically, we focus on the modeling of continuous states, continuous actions and supporting rewards for an optimized recognition. We also present an algorithm for the sequential fusion of gathered image information and we combine all these components into a single framework. The experimental evaluations are split into results for synthetic and real objects with one- or two-dimensional camera actions, respectively. This allows the systematic evaluation of the theoretical correctness as well as the practical applicability of the proposed method. Our experiments showed that the proposed combined viewpoint selection and viewpoint fusion approach is able to significantly improve the recognition rates compared to passive object recognition with randomly chosen views.

A New System for Monitoring Gait Training in Infants With Down Syndrome

Infants with Down syndrome show an altered pattern of motor development at early childhood. Treadmill-walking training can be used to promote the earlier attainment of motor milestones in infants with locomotion deficiencies but quantitative data on their motor development are limited to gait laboratory studies. Our purpose was to develop, validate, and test a low-cost portable system for detecting infant steps on a treadmill while training. The system includes five infrared distance sensors, which were placed on a motorized treadmill to record the location of the feet of the infant during walking and thus measure his/her step length and cadence. The system was validated using synthetic objects, with a healthy 13-month-old infant. Pilot studies were then conducted in additional five infants with Down syndrome (aged 11–28 months) to determine step length (17.5–22.3 cm) and cadence (0.33–2.16 steps/s) at baseline, as well as at follow-ups 1 month and 3 months after the first trial. Measurements were repeatable per session and agreed with values reported in the literature. These pilot studies indicate the potential utility of the present system in quantitative monitoring of the process of acquisition of initial gait in infants with Down syndrome at the care facility where routine therapy is given.

A psychophysical investigation of global illumination algorithms used in augmented reality

The overarching goal of this research was to compare different rendering solutions in order to understand why some yield better results specifically when applied to rendering synthetic objects into real photographs. A psychophysical experiment was conducted in which the composite images were judged for accuracy against the original photograph. In addition, iCAM, an image color appearance model was also used to calculate image differences for the same set of images. Conclusions obtained included the effect of global illumination on the accuracy of the final composite rendering. Also, it was discovered that the original rendering with all of its artifacts is not necessarily an indicator of the final composite image's judged accuracy. Finally, initial results show promise in using iCAM to predict a relationship similar to the psychophysics, which could eventually be used in-the-rendering-loop to achieve photorealism with minimized computation.

Accurate shape from focus based on focus adjustment in optical microscopy

Optical microscopy allows a magnified view of the sample while decreasing the depth of focus. Although the acquired images from limited depth of field have both blurred and focused regions, they can provide depth information. The technique to estimate the depth and 3D shape of an object from the images of the same sample obtained at different focus settings is called shape from focus (SFF). In SFF, the measure of focus--sharpness--is the crucial part for final 3D shape estimation. The conventional methods compute sharpness by applying focus measure operator on each 2D image frame of the image sequence. However, such methods do not reflect the accurate focus levels in an image because the focus levels for curved objects require information from neighboring pixels in the adjacent frames too. To address this issue, we propose a new method based on focus adjustment which takes the values of the neighboring pixels from the adjacent image frames that have approximately the same initial depth as of the center pixel and then it re-adjusts the center value accordingly. Experiments were conducted on synthetic and microscopic objects, and the results show that the proposed technique generates better shape and takes less computation time in comparison with previous SFF methods based on focused image surface (FIS) and dynamic programming.

Axial superresolution by synthetic aperture generation

The use of tilted illumination onto the input object in combination with time multiplexing is a useful technique to overcome the Abbe diffraction limit in imaging systems. It is based on the generation of an expanded synthetic aperture that improves the cutoff frequency (and thus the resolution limit) of the imaging system. In this paper we present an experimental validation of the fact that the generation of a synthetic aperture improves not only the lateral resolution but also the axial one. Thus, it is possible to achieve higher optical sectioning of three-dimensional (3D) objects than that defined by the theoretical resolution limit imposed by diffraction. Experimental results are provided for two different cases: a synthetic object (micrometer slide) imaged by a 0.14 numerical aperture (NA) microscope lens, and a biosample (swine sperm cells) imaged by a 0.42 NA objective.

Light field transfer

We present a novel image-based method for compositing real and synthetic objects in the same scene with a high degree of visual realism. Ours is the first technique to allow global illumination and near-field lighting effects between both real and synthetic objects at interactive rates, without needing a geometric and material model of the real scene. We achieve this by using a light field interface between real and synthetic components---thus, indirect illumination can be simulated using only two 4D light fields, one captured from and one projected onto the real scene. Multiple bounces of interreflections are obtained simply by iterating this approach. The interactivity of our technique enables its use with time-varying scenes, including dynamic objects. This is in sharp contrast to the alternative approach of using 6D or 8D light transport functions of real objects, which are very expensive in terms of acquisition and storage and hence not suitable for real-time applications. In our method, 4D radiance fields are simultaneously captured and projected by using a lens array, video camera, and digital projector. The method supports full global illumination with restricted object placement, and accommodates moderately specular materials. We implement a complete system and show several example scene compositions that demonstrate global illumination effects between dynamic real and synthetic objects. Our implementation requires a single point light source and dark background.

Hybrid linear dendritic macromolecules: From synthesis to applications

AbstractLinear‐dendritic copolymers are intriguing macromolecules, which offer challenge and fascination as purely synthetic objects at the crossroad of organic and polymer chemistry and as promising materials for diverse advanced applications. This review traces their discovery and highlights the synthetic strategies used for their construction. The ambivalent character of the linear‐dendritic architecture opens numerous avenues towards emerging and potential applications. Specific solution properties enable the construction of nanometer‐sized nanoreactors for reactions in environmentally friendly media, and the creation of “nanosponges” for selective passive binding of fluorescent pH‐indicators for environmental or biomonitoring. Another structure–property relationship is used for noncovalent and site‐specific modification of glycoproteins, which leads to the formation of “semiartificial” enzymes with enhanced and broadened catalytic activity. © 2008 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 46: 5295–5314, 2008

Applications of ICA for the enhancement and classification of polarimetric SAR images

Independent components analysis (ICA) based methods for polarimetric synthetic aperture radar (SAR) image speckle reduction and ground object classification are studied. Several independent components can be extracted from polarimetric SAR images using ICA directly. The component with lowest speckle index is regarded as the scene after speckle reduction. The disadvantage of this method is that only one image is kept and most polarization information will be lost. In this paper, we use ICA‐sparse‐coding shrinkage (ICA‐SPS) based speckle reduction method, which is implemented on each individual image and can keep polarization information. It is carried out on the combined channels obtained by Pauli‐decomposition rather than original polarization channels in order to keep relative phase information among polarization channels and get better performance. After ICA‐SPS, the effect of speckle suppression on SAR image classification can be compared favourably with other methods by combining the channels into a false colour image. At last, a new ICA‐based classification method is presented. In this method, four independent components are separated by ICA from five polarization and combined channels. One of these independent components which includes little ground object information is regarded as speckle noise and therefore be discarded. The remaining three components can be treated as subordination coefficients of three kinds of targets. A classified image can be obtained based on the components. And by composing these three channels in RGB colour pattern, a false colour image can be constructed.

Estimation of multiple directional illuminants from a single image

We present a new method for the detection and estimation of multiple directional illuminants, using only one single image of an object with known geometry. It obviates the need to modify the imaged scene by inserting calibration objects of any particular geometry, relying instead on partial knowledge of the geometry of the scene. We first develop our method for the case of a Lambertian sphere with known size, illuminated by a set of directional light sources. A novel and robust way is proposed to segment the surface into regions, with each region illuminated by a different set of sources. Our region-based least-squares method is impervious to noise and missing data, which is crucial to extending the method to arbitrary smooth geometry and to surfaces having both Lambertian and specular properties. We propose a novel methodology that integrates information from shadows and shading in the presence of strong directional sources of illumination, even when significant non-directional sources exist in the scene and the object surface is not Lambertian. We demonstrate experimentally the accuracy of our method, both in detecting the number of light sources and in estimating their directions, by testing on images of a variety of synthetic and real objects.

Key-Frame Selection and an LMedS-Based Approach to Structure and Motion Recovery

Auto-calibration for structure and motion recovery can be used for match move where the goal is to insert synthetic 3D objects into real scenes and create views as if they were part of the real scene. However, most auto-calibration methods for multi-views utilize bundle adjustment with non-linear optimization, which requires a very good starting approximation. We propose a novel key-frame selection measurement and LMedS (Least Median of Square)-based approach to estimate scene structure and motion from image sequences captured with a hand-held camera. First, we select key-frames considering the ratio of number of correspondences and feature points, the homography error and the distribution of corresponding points in the image. Then, by using LMedS, we reject erroneous frames among the key-frames in absolute quadric estimation. Simulation results demonstrated that the proposed method can select suitable key-frames efficiently and achieve more precise camera pose estimation without non-linear optimization.

A finite element method for animating large viscoplastic flow

We present an extension to Lagrangian finite element methods to allow for large plastic deformations of solid materials. These behaviors are seen in such everyday materials as shampoo, dough, and clay as well as in fantastic gooey and blobby creatures in special effects scenes. To account for plastic deformation, we explicitly update the linear basis functions defined over the finite elements during each simulation step. When these updates cause the basis functions to become ill-conditioned, we remesh the simulation domain to produce a new high-quality finite-element mesh, taking care to preserve the original boundary. We also introduce an enhanced plasticity model that preserves volume and includes creep and work hardening/softening. We demonstrate our approach with simulations of synthetic objects that squish, dent, and flow. To validate our methods, we compare simulation results to videos of real materials.

Spatially varying image based lighting by light probe sequences

We present a novel technique for capturing spatially or temporally resolved light probe sequences, and using them for image based lighting. For this purpose we have designed and built a real-time light probe, a catadioptric imaging system that can capture the full dynamic range of the lighting incident at each point in space at video frame rates, while being moved through a scene. The real-time light probe uses a digital imaging system which we have programmed to capture high quality, photometrically accurate color images of 512×512 pixels with a dynamic range of 10000000:1 at 25 frames per second. By tracking the position and orientation of the light probe, it is possible to transform each light probe into a common frame of reference in world coordinates, and map each point and direction in space along the path of motion to a particular frame and pixel in the light probe sequence. We demonstrate our technique by rendering synthetic objects illuminated by complex real world lighting, first by using traditional image based lighting methods and temporally varying light probe illumination, and second an extension to handle spatially varying lighting conditions across large objects and object motion along an extended path.

Noise distribution in SENSE- and GRAPPA-reconstructed images: a computer simulation study

This work presents a descriptive study of noise distributions in images reconstructed according to the parallel imaging methods SENSE and GRAPPA. In the computer simulations, two different settings were used for describing an object. The first setting included a synthetic object and eight complex-valued coil sensitivities. In the second setting, a complex-valued in vitro object, composed of four individual coil images, was used. After adding noise and subsampling k-space for each coil image, reconstruction was performed according to SENSE, with and without regularization, and GRAPPA for different reduction factors. A set of images was created for three different reduction factors. Noise distributions were determined for each data set and compared with each other. The results of this study show that the noise distributions in SENSE- and GRAPPA-reconstructed images differ. The noise in images reconstructed according to GRAPPA has a more uniform spatial distribution compared with SENSE-reconstructed images, in which the noise varies regionally according to the geometry factor. The noise distribution in SENSE-reconstructed images using regularization showed a similar but lowered pattern of noise compared with images reconstructed according to SENSE without regularization.

Context-aware textures

Interesting textures form on the surfaces of objects as the result of external chemical, mechanical, and biological agents. Simulating these textures is necessary to generate models for realistic image synthesis. The textures formed are progressively variant, with the variations depending on the global and local geometric context. We present a method for capturing progressively varying textures and the relevant context parameters that control them. By relating textures and context parameters, we are able to transfer the textures to novel synthetic objects. We present examples of capturing chemical effects, such as rusting; mechanical effects, such as paint cracking; and biological effects, such as the growth of mold on a surface. We demonstrate a user interface that provides a method for specifying where an object is exposed to external agents. We show the results of complex, geometry-dependent textures evolving on synthetic objects.

Representation and reconstruction of fuzzy disks by moments

In this paper, we analyze the representation and reconstruction of fuzzy disks by using moments. Both continuous and digital fuzzy disks are considered. A fuzzy disk is a convex fuzzy spatial set, where the membership of a point to the fuzzy disk depends only on the distance of the point to the centre of the disk. We show that, for a certain class of membership functions defining a fuzzy disk, there exists a one-to-one correspondence between the set of fuzzy disks and the set of their generalized moment representations. Theoretical error bounds for the accuracy of the estimation of generalized moments of a continuous fuzzy disk from the generalized moments of its digitization and, in connection with that, the accuracy of an approximate reconstruction of a continuous fuzzy disk from the generalized moments of its digitization, are derived. Defuzzification (reduction of a continuous fuzzy disk to a crisp representative) is also considered. A statistical study of generated synthetic objects complements the theoretical results.

Watermark recovery from two-dimensional views of a three-dimensional object using texture or silhouette information

We describe a novel framework for watermarking 3-D objects using their texture or silhouette information. Unlike most conventional 3-D object-watermarking techniques, for which both insertion and extraction of the mark are performed on the object itself (3-D/3-D approach), we propose an asymmetric 3-D/2-D procedure. It consists in watermarking 3-D objects and retrieving the mark from rendering 2-D images or videos having used the 3-D synthetic object, thus protecting the visual representations of the object. Two 3-D object watermarking schemes are presented, a texture-based approach for 3-D photorealistic objects and a silhouette-based approach for 3-D CAD (computer-assisted design) objects.