46437694
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.
6932570
3D Surface Matching and Recognition Using Conformal Geometry
3D surface matching is a fundamental issue in computer vision with many applications such as shape registration, 3D object recognition and classification. However, surface matching with noise, occlusion and clutter is a challenging problem. In this paper, we analyze a family of conformal geometric maps including harmonic maps, conformal maps and least squares conformal maps with regards to 3D surface matching. As a result, we propose a novel and computationally efficient surface matching framework that uses least squares conformal maps. According to conformal geometry theory, each 3D surface with disk topology can be mapped to a 2D domain through a global optimization and the resulting map is a diffeomorphism, i.e., one-to-one and onto. This allows us to simplify the 3D surface-matching problem to a 2D image-matching problem, by comparing the resulting 2D conformal geometric maps, which are stable, insensitive to resolution changes and robust to occlusion and noise. Therefore, highly accurate and efficient 3D surface matching algorithms can be achieved by using conformal geometric maps. Finally, the performance of conformal geometric maps is evaluated and analyzed comprehensively in 3D surface matching with occlusion, noise and resolution variation. We also provide a series of experiments on real 3D face data that achieve high recognition rates.
19020033
Estimation of multiple directional light sources for synthesis of augmented reality images
We present a new method for the detection and estimation of multiple directional illuminants, using a single image of any object with known geometry and Lambertian reflectance. We use the resulting highly accurate estimates to modify virtually the illumination and geometry of a real scene and produce correctly illuminated mixed reality images. Our method 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. Thus, the recovered multiple illuminants can be used both for image-based rendering and for shape reconstruction. Our method combines information both from the shading of the object and from shadows cast on the scene by the object. Initially we use a method based on shadows and a method based on shading independently. The shadow based method utilizes brightness variation inside the shadows cast by the object, whereas the shading based method utilizes brightness variation on the directly illuminated portions of the object. We demonstrate how the two sources of information complement each other in a number of occasions. We then describe an approach that integrates the two methods, with results superior to those obtained if the two methods are used separately. The resulting illumination information can be used (i) to render synthetic objects in a real photograph with correct illumination effects, and (ii) to virtually re-light the scene.
6287453
A dynamic assignment problem in a mobile system with limited bandwidth
The assignment problem originally arising from parallel and distributed computing has been investigated intensively since the 70's when Harold Stone proposed a method to solve it with the aid of network flow algorithms. In this paper, we discuss this problem under a mobile environment with limited capacity of wireless links. The assignment problem is to schedule a group of related objects from a resource-constrained mobile device to its powerful proxy machine so that program activity migrates among processors as execution proceeds, and hence the overall performance will improve. First, we reduce this optimization problem to the 0/1 knapsack problem, and therefore show that it is NP-hard. Second, two heuristic algorithms are proposed. One is an adaptive heuristic algorithm with complexity O(NE), here, N and E represent the number of nodes and edges in the object graph abstracted from the mobile application. The other is a non-adaptive heuristic algorithm with complexity O(E), i.e, N times faster than the adaptive counterpart. Finally, we provide a simple distributed algorithm based on Raymond's tree-based distributed mutual exclusion algorithm for solving this problem with message complexity O(N/sup 2/ log N).
5756583
Face Relighting from a Single Image under Arbitrary Unknown Lighting Conditions
In this paper, we present a new method to modify the appearance of a face image by manipulating the illumination condition, when the face geometry and albedo information is unknown. This problem is particularly difficult when there is only a single image of the subject available. Recent research demonstrates that the set of images of a convex Lambertian object obtained under a wide variety of lighting conditions can be approximated accurately by a low-dimensional linear subspace using a spherical harmonic representation. Moreover, morphable models are statistical ensembles of facial properties such as shape and texture. In this paper, we integrate spherical harmonics into the morphable model framework by proposing a 3D spherical harmonic basis morphable model (SHBMM). The proposed method can represent a face under arbitrary unknown lighting and pose simply by three low-dimensional vectors, i.e., shape parameters, spherical harmonic basis parameters, and illumination coefficients, which are called the SHBMM parameters. However, when the image was taken under an extreme lighting condition, the approximation error can be large, thus making it difficult to recover albedo information. In order to address this problem, we propose a subregion-based framework that uses a Markov random field to model the statistical distribution and spatial coherence of face texture, which makes our approach not only robust to extreme lighting conditions, but also insensitive to partial occlusions. The performance of our framework is demonstrated through various experimental results, including the improved rates for face recognition under extreme lighting conditions.
5690166
Developing a database for proteomic analysis of extracytosolic plant proteins
Extracytosolic plant proteins are involved in numerous processes including nutrient acquisition, communication with other soil organisms, protection from pathogens, and resistant to disease and toxic metals. We have developed an online database to provide the plant biology community with relevant information about extracytosolic plant proteins. Data for Brassica napus (canola) proteins identified using proteomics tools can be accessed using this database. Several textual and graphical query capabilities allow biologists to populate and query this database. Results are displayed with active links to other databases. The system has an open API allowing other applications to access this database as a Web service. In addition, the database is augmented with a repository of tools that can be used in data analysis and mining tasks.
17669846
Research on the Robustness of a Proportional Integral Switching Surface Based on Sliding Mode Control
In this paper, a novel proportional-integral (PI) switching surface is introduced for determining the synchronization performance of systems in the sliding mode motion. Based on the sliding mode controller, the system is established by a robust control scheme which guarantees the occurrence of a sliding motion of error states even when the parameter uncertainty and external disturbance are present. So this paper researches on robust synchronization problem by investigating a highly complex dynamic nonlinear system—chaotic systems. Some simulation results on controlling different chaotic systems are made and investigated in order to demonstrate the good performance of the method and this control design process is much easier to be completed.
8808466
Joint region tracking with switching hypothesized measurements
We propose a switching hypothesized measurements (SHM) model supporting multimodal probability distributions and present the application of the model in handling potential variability in visual environments when tracking multiple objects jointly. For a set of occlusion hypotheses, a frame is measured once under each hypothesis, resulting in a set of measurements at each time instant. A computationally efficient SHM filter is derived for online joint region tracking. Both occlusion relationships and states of the objects are recursively estimated from the history of hypothesized measurements. The reference image is updated adaptively to deal with appearance changes of the objects. The SHM model is generally applicable to various dynamic processes with multiple alternative measurement methods.
15156880
Adaptive Foreground and Shadow Detection in Image Sequences
This paper presents a novel method of foreground segmentation that distinguishes moving objects from their moving cast shadows in monocular image sequences. The models of background, edge information, and shadow are set up and adaptively updated. A Bayesian belief network is proposed to describe the relationships among the segmentation label, background, intensity, and edge information. The notion of Markov random field is used to encourage the spatial connectivity of the segmented regions. The solution is obtained by maximizing the posterior possibility density of the segmentation field.
2358468
Human Action Recognition by Semilatent Topic Models
We propose two new models for human action recognition from video sequences using topic models. Video sequences are represented by a novel "bag-of-words" representation, where each frame corresponds to a "word". Our models differ from previous latent topic models for visual recognition in two major aspects: first of all, the latent topics in our models directly correspond to class labels; second, some of the latent variables in previous topic models become observed in our case. Our models have several advantages over other latent topic models used in visual recognition. First of all, the training is much easier due to the decoupling of the model parameters. Second, it alleviates the issue of how to choose the appropriate number of latent topics. Third, it achieves much better performance by utilizing the information provided by the class labels in the training set. We present action classification results on five different data sets. Our results are either comparable to, or significantly better than previously published results on these data sets.
12377491
An Intelligent Language Tutoring System for Handling Errors Caused by Transfer
This research addresses how an Intelligent Language Tutoring System can effectively help to solve a practical problem of transfer in students' second language learning of Chinese. Our empirical data shows that the problem of transfer accounts for most of the errors observed in the linguistic output of English-speaking students in their study of Chinese. This accords with views of other experts on transfer in the field of second language learning, such as Selinker [15], Cornu [6], Sheen [16] and Cowan [7]. A technique of mixed grammar of Chinese and English is used to tackle the problem of transfer. In this paper, we describe the importance of transfer, explain the data that has been collected, present an overview of the three main models, demonstrate the technique that we use to handle errors of transfer and finally discuss how our system is going to be evaluated.