13897908
Detail preserving shape deformation in image editing
Shape deformation is a common practice in digital image editing, but can unrealistically stretch or compress texture detail. We propose an image editing system that decouples feature position from pixel color generation, by resynthesizing texture from the source image to preserve its detail and orientation around a new feature curve location. We introduce a new distortion to patch-based texture synthesis that aligns texture features with image features. A dense correspondence field between source and target images generated by the control curves then guides texture synthesis.
13249098
Automatic alignment of large-scale aerial rasters to road-maps
This paper introduces a practical approach to register large-scale GIS imagery to a database of road vectors automatically. The proposed approach breaks the global alignment problem into a set of localized domains (tiles). Within each tile, the displacement between imagery and vectors is approximated by a translation. Finally, a global thin-plate-spline warp based on these local approximations is applied to register the imagery to the vector data.
 The critical step in this approach is a fully automatic algorithm to compute the best imagery-to-vectors translation within a tile. The proposed algorithm performs vector-guided extraction of road features, aggregates features obtained in the neighborhood of multiple vectors, and then estimates the best translation through a least-squares optimization applied to a selected subset of the aggregated features. It also computes a confidence value for each processed image tile, so that a human operator can easily find out the places where the automatic approach has encountered difficulties, if necessary. The algorithm has been tested on hundreds of production satellite images of different countries. It has correctly registered over 80 percent of the imagery, and consistently reported low confidence values for the rest.
5098005
RotoTexture: Automated Tools for Texturing Raw Video
We propose a video editing system that allows a user to apply a time-coherent texture to a surface depicted in the raw video from a single uncalibrated camera, including the surface texture mapping of a texture image and the surface texture synthesis from a texture swatch. Our system avoids the construction of a 3D shape model and instead uses the recovered normal field to deform the texture so that it plausibly adheres to the undulations of the depicted surface. The texture mapping method uses the nonlinear least-squares optimization of a spring model to control the behavior of the texture image as it is deformed to match the evolving normal field through the video. The texture synthesis method uses a coarse optical flow to advect clusters of pixels corresponding to patches of similarly oriented surface points. These clusters are organized into a minimum advection tree to account for the dynamic visibility of clusters. We take a rather crude approach to normal recovering and optical flow estimation, yet the results are robust and plausible for nearly diffuse surfaces such as faces and t-shirts
7037192
Interactive material replacement in photographs
Material replacement has wide application throughout the entertainment industry, particularly for post-production make-up application or wardrobe adjustment. More generally, any low-cost mock-up object can be processed to have the appearance of expensive, high-quality materials. We demonstrate a new system that allows fast, intuitive material replacement in photographs. We extend recent work in object selection and fast texture synthesis, as well as develop a novel approach to shape-from-shading capable of handling objects with albedo changes. Each component of our system runs with interactive speed, allowing for easy experimentation and refinement of results.
8559794
Randomly accessible procedural animation of physically approximate turbulent motion
Complex virtual environments can be simulated with physical or procedural motion. Physical motion is more realistic, but requires the integration of an ordinary differential equation from an initial state. Procedural motion has the advantage of being randomly accessible, though it is not physically based. We combine these techniques into a multiresolution model. A coarse-level simulation is sampled to yield keyframes. Then a physical motion between keyframes is calculated and distorted to meet its boundary conditions. We demonstrate these ideas with a simple virtual world consisting of wind blowing trees and leaves that can be entered and experienced efficiently at any point in time.
16979811
Neural adaptive control for a class of nonlinear systems with unknown deadzone
This paper focuses on the adaptive control of a class of nonlinear systems with unknown deadzone using neural networks. By constructing a deadzone pre-compensator, a neural adaptive control scheme is developed using backstepping design techniques. Transient performance is guaranteed and semi-globally uniformly ultimately bounded stability is obtained. Another feature of this scheme is that the neural networks reconstruction error bound is assumed to be unknown and can be estimated online. Simulation results are given to demonstrate the effectiveness of the proposed controller.
1454940
Video Indexing and Retrieval in Compressed Domain Using Fuzzy-Categorization
There has been an increased interest in video indexing and retrieval in recent years. In this work, indexing and retrieval system of the visual contents is based on feature extracted from the compressed domain. Direct possessing of the compressed domain spares the decoding time, which is extremely important when indexing large number of multimedia archives. A fuzzy-categorizing structure is designed in this paper to improve the retrieval performance. In our experiment, a database that consists of basketball videos has been constructed for our study. This database includes three categories: full-court match, penalty and close-up. First, spatial and temporal feature extraction is applied to train the fuzzy membership functions using the minimum entropy optimal algorithm. Then, the max composition operation is used to generate a new fuzzy feature to represent the content of the shots. Finally, the fuzzy-based representation becomes the indexing feature for the content-based video retrieval system. The experimental results show that the proposal algorithm is quite promising for semantic-based video retrieval.
11027312
An Implementation of Time and Frequency Synchronization for Carrier Interferometry of OFDM in an Underwater Acoustic Channel
Considering the features of Underwater Acoustic channel and the sensitivity versus synchronization for CI/OFDM system, A time and frequency synchronization method based on Constant Amplitude Zero Auto-Correlation(CAZAC) sequence is presented. The time offset estimation and carrier frequency offset estimation can be achieved simultaneously. The fractional part and integral part of carrier offset estimation can be respectively got by the correlation result of time offset estimation and cyclic correlation principle. The efficacy of the synchronization algorithms is demonstrated experimentally.
17735204
3D Face Reconstruction Under Imperfect Tracking Circumstances Using Shape Model Constraints
We propose a factorization structure from motion (SfM) framework which employs 3D active shape constraints for a 3D face model application. Two types of shape model, individual shape models and a generic model, are used to approximate non-linear manifold variation. When the 3D shape models are trained, they help the SfM algorithm to reconstruct the 3D face structure under noisy observation (tracking) circumstances. By minimizing two sets of errors, the reconstruction error generated by the linear transform of the shape models and projection error obtained by re-projecting the 3D shape to 2D positions, the 3D face shapes can be recovered optimally. Experimental results show that this algorithm accurately reconstructs the 3D shape of familiar and non-familiar faces from video sequences under circumstances of imperfect face tracking or noisy observations.
1496316
Determination of Total Amino Acids in Oilseed Rape Leaves Using Near Infrared Spectroscopy and Chemometrics
Near infrared spectroscopy combined with chemometrics was investigated to determine the total amino acids (TAA) in oilseed rape leaves. The samples in calibration, validation and prediction set were 80, 40 and 30, respectively. Different spectral preprocessing were compared, and three calibration methods were employed including partial least squares (PLS), multiple linear regression (MLR) and least squares-support vector machine (LS-SVM). The performance evaluation standards were determination coefficients (R2) and root mean square error (RMSE). Successive projections algorithm (SPA) was applied as variable selection method. The optimal model was achieved by SPA-LS-SVM using 13 relevant wavelengths with R2 = 0.9830 and RMSEP = 0.3964. The LS-SVM outperformed PLS and SPA-MLR models. The results indicated that near infrared spectroscopy was successfully applied for the determination of TAA in oilseed rape leaves. This detection method could be used for the on field monitoring of growing status and other physiological parameters of oilseed rape.