Sensing through body dynamics

It has been shown that sensory morphology and sensory-motor coordination enhance the capabilities of sensing in robotic systems. The tasks of categorization and category learning, for example, can be significantly simplified by exploiting the morphological constraints, sensory-motor couplings and the interaction with the environment. This paper argues that, in the context of sensory-motor control, it is essential to consider body dynamics derived from morphological properties and the interaction with the environment in order to gain additional insight into the underlying mechanisms of sensory-motor coordination, and more generally the nature of perception. A locomotion model of a four-legged robot is used for the case studies in both simulation and real world. The locomotion model demonstrates how attractor states derived from body dynamics influence the sensory information, which can then be used for the recognition of stable behavioral patterns and of physical properties in the environment. A comprehensive analysis of behavior and sensory information leads to a deeper understanding of the underlying mechanisms by which body dynamics can be exploited for category learning of autonomous robotic systems. © 2006 Elsevier Ltd. All rights reserved.

A novel image restoration algorithm based on high-dimensional space geometry

A novel image restoration approach based on high-dimensional space geometry is proposed, which is quite different from the existing traditional image restoration techniques. It is based on the homeomorphisms and "Principle of Homology Continuity" (PHC), an image is mapped to a point in high-dimensional space. Begin with the original blurred image, we get two further blurred images, then the restored image can be obtained through the regressive curve derived from the three points which are mapped form the images. Experiments have proved the availability of this "blurred-blurred-restored" algorithm, and the comparison with the classical Wiener Filter approach is presented in final.

A novel image restoration algorithm based on high-dimensional space geometry

A novel image restoration approach based on high-dimensional space geometry is proposed, which is quite different from the existing traditional image restoration techniques. It is based on the homeomorphisms and "Principle of Homology Continuity" (PHC), an image is mapped to a point in high-dimensional space. Begin with the original blurred image, we get two further blurred images, then the restored image can be obtained through the regressive curve derived from the three points which are mapped form the images. Experiments have proved the availability of this "blurred-blurred-restored" algorithm, and the comparison with the classical Wiener Filter approach is presented in final.

Synthesis and application on parallel image storage of bisfurylfulgide

A bisfurylfulgide, E, E-3,4-bis[1-(2,5-dimethyl-3-furyl)ethylidene]-3,4-dihydrofuran-2,5-dione, is synthesized by Stobbe condensation reaction. The molecular structure of target compound is confirmed by single crystal X-ray crystallography analysis. It shows that the distances between two possible reaction sites of molecule are 0.3394 and 0.3406 nm respectively, which is favorable to photocyclization. The photochromic properties of this compound in different solvents are investigated, and the result shows that the compound exhibits excellent photochromic behavior. The primary result of applied research on parallel image storage is also presented.

超参数控制下的波阻抗约束反演

The seismic survey is the most effective geophysical method during exploration and development of oil/gas. As a main means in processing and interpreting seismic data, impedance inversion takes up a special position in seismic survey. This is because the impedance parameter is a ligament which connects seismic data with well-logging and geological information, while it is also essential in predicting reservoir properties and sand-body. In fact, the result of traditional impedance inversion is not ideal. This is because the mathematical inverse problem of impedance is poor-pose so that the inverse result has instability and multi-result, so it is necessary to introduce regularization. Most simple regularizations are presented in existent literature, there is a premise that the image(or model) is globally smooth. In fact, as an actual geological model, it not only has made of smooth region but also be separated by the obvious edge, the edge is very important attribute of geological model. It's difficult to preserve these characteristics of the model and to avoid an edge too smooth to clear. Thereby, in this paper, we propose a impedance inverse method controlled by hyperparameters with edge-preserving regularization, the inverse convergence speed and result would be improved. In order to preserve the edge, the potential function of regularization should satisfy nine conditions such as basic assumptions edge preservation and convergence assumptions etc. Eventually, a model with clear background and edge-abnormity can be acquired. The several potential functions and the corresponding weight functions are presented in this paper. The potential functionφLφHL andφGM can meet the need of inverse precision by calculating the models. For the local constant planar and quadric models, we respectively present the neighborhood system of Markov random field corresponding to the regularization term. We linearity nonlinear regularization by using half-quadratic regularization, it not only preserve the edge, and but also simplify the inversion, and can use some linear methods. We introduced two regularization parameters (or hyperparameters) λ2 and δ in the regularization term. λ2 is used to balance the influence between the data term and the transcendental term; δ is a calibrating parameter used to adjust the gradient value at the discontinuous position(or formation interface). Meanwhile, in the inverse procedure, it is important to select the initial value of hyperparameters and to change hyperparameters, these will then have influence on convergence speed and inverse effect. In this paper, we roughly give the initial value of hyperparameters by using a trend- curve of φ-(λ2, δ) and by a method of calculating the upper limit value of hyperparameters. At one time, we change hyperparameters by using a certain coefficient or Maximum Likelihood method, this can be simultaneously fulfilled with the inverse procedure. Actually, we used the Fast Simulated Annealing algorithm in the inverse procedure. This method overcame restrictions from the local extremum without depending on the initial value, and got a global optimal result. Meanwhile, we expound in detail the convergence condition of FSA, the metropolis receiving probability form Metropolis-Hasting, the thermal procession based on the Gibbs sample and other methods integrated with FSA. These content can help us to understand and improve FSA. Through calculating in the theoretic model and applying it to the field data, it is proved that the impedance inverse method in this paper has the advantage of high precision practicability and obvious effect.

用宽频带远震体波波形研究中国及邻近地区地壳构造及地质意义初探

The theory and approach of the broadband teleseismic body waveform inversion are expatiated in this paper, and the defining the crust structure's methods are developed. Based on the teleseismic P-wave data, the theoretic image of the P-wave radical component is calculated via the convolution of the teleseismic P-wave vertical component and the transform function, and thereby a P-wavefrom inversion method is built. The applied results show the approach effective, stable and its resolution high. The exact and reliable teleseismic P waveforms recorded by CDSN and IRIS and its geodynamics are utilized to obtain China and its vicinage lithospheric transfer functions, this region ithospheric structure is inverted through the inversion of reliable transfer functions, the new knowledge about the deep structure of China and its vicinage is obtained, and the reliable seismological evidence is provided to reveal the geodynamic evolution processes and set up the continental collisional theory. The major studies are as follows: Two important methods to study crustal and upper mantle structure -- body wave travel-time inversion and waveform modeling are reviewed systematically. Based on ray theory, travel-time inversion is characterized by simplicity, crustal and upper mantle velocity model can be obtained by using 1-D travel-time inversion preliminary, which introduces the reference model for studying focal location, focal mechanism, and fine structure of crustal and upper mantle. The large-scale lateral inhomogeneity of crustal and upper mantle can be obtained by three-dimensional t ravel-time seismic tomography. Based on elastic dynamics, through the fitting between theoretical seismogram and observed seismogram, waveform modeling can interpret the detail waveform and further uncover one-dimensional fine structure and lateral variation of crustal and upper mantle, especially the media characteristics of singular zones of ray. Whatever travel-time inversion and waveform modeling is supposed under certain approximate conditions, with respective advantages and disadvantages, and provide convincing structure information for elucidating physical and chemical features and geodynamic processes of crustal and upper mantle. Because the direct wave, surface wave, and refraction wave have lower resolution in investigating seismic velocity transitional zone, which is inadequate to study seismic discontinuities. On the contrary, both the converse and reflected wave, which sample the discontinuities directly, must be carefully picked up from seismogram to constrain the velocity transitional zones. Not only can the converse wave and reflected wave study the crustal structure, but also investigate the upper mantle discontinuities. There are a number of global and regional seismic discontinuities in the crustal and upper mantle, which plays a significant role in understanding physical and chemical properties and geodynamic processes of crustal and upper mantle. The broadband teleseismic P waveform inversion is studied particularly. The teleseismic P waveforms contain a lot of information related to source time function, near-source structure, propagation effect through the mantle, receiver structure, and instrument response, receiver function is isolated form teleseismic P waveform through the vector rotation of horizontal components into ray direction and the deconvolution of vertical component from the radial and tangential components of ground motion, the resulting time series is dominated by local receiver structure effect, and is hardly irrelevant to source and deep mantle effects. Receiver function is horizontal response, which eliminate multiple P wave reflection and retain direct wave and P-S converted waves, and is sensitive to the vertical variation of S wave velocity. Velocity structure beneath a seismic station has different response to radial and vertical component of an accident teleseismic P wave. To avoid the limits caused by a simplified assumption on the vertical response, the receiver function method is mended. In the frequency domain, the transfer function is showed by the ratio of radical response and vertical response of the media to P wave. In the time domain, the radial synthetic waveform can be obtained by the convolution of the transfer function with the vertical wave. In order to overcome the numerical instability, generalized reflection and transmission coefficient matrix method is applied to calculate the synthetic waveform so that all multi-reflection and phase conversion response can be included. A new inversion method, VFSA-LM method, is used in this study, which successfully combines very fast simulated annealing method (VFSA) with damped least square inversion method (LM). Synthetic waveform inversion test confirms its effectiveness and efficiency. Broadband teleseismic P waveform inversion is applied in lithospheric velocity study of China and its vicinage. According to the data of high quality CDSN and IRIS, we obtained an outline map showing the distribution of Asian continental crustal thickness. Based on these results gained, the features of distribution of the crustal thickness and outline of crustal structure under the Asian continent have been analyzed and studied. Finally, this paper advances the principal characteristics of the Asian continental crust. There exist four vast areas of relatively minor variations in the crustal thickness, namely, northern, eastern southern and central areas of Asian crust. As a byproduct, the earthquake location is discussed, Which is a basic issue in seismology. Because of the strong trade-off between the assumed initial time and focal depth and the nonlinear of the inversion problems, this issue is not settled at all. Aimed at the problem, a new earthquake location method named SAMS method is presented, In which, the objective function is the absolute value of the remnants of travel times together with the arrival times and use the Fast Simulated Annealing method is used to inverse. Applied in the Chi-Chi event relocation of Taiwan occurred on Sep 21, 2000, the results show that the SAMS method not only can reduce the effects of the trade-off between the initial time and focal depth, but can get better stability and resolving power. At the end of the paper, the inverse Q filtering method for compensating attenuation and frequency dispersion used in the seismic section of depth domain is discussed. According to the forward and inverse results of synthesized seismic records, our Q filtrating operator of the depth domain is consistent with the seismic laws in the absorbing media, which not only considers the effect of the media absorbing of the waves, but also fits the deformation laws, namely the frequency dispersion of the body wave. Two post stacked profiles about 60KM, a neritic area of China processed, the result shows that after the forward Q filtering of the depth domain, the wide of the wavelet of the middle and deep layers is compressed, the resolution and signal noise ratio are enhanced, and the primary sharp and energy distribution of the profile are retained.

Inferring 3D Structure with a Statistical Image-Based Shape Model

We present an image-based approach to infer 3D structure parameters using a probabilistic "shape+structure'' model. The 3D shape of a class of objects may be represented by sets of contours from silhouette views simultaneously observed from multiple calibrated cameras. Bayesian reconstructions of new shapes can then be estimated using a prior density constructed with a mixture model and probabilistic principal components analysis. We augment the shape model to incorporate structural features of interest; novel examples with missing structure parameters may then be reconstructed to obtain estimates of these parameters. Model matching and parameter inference are done entirely in the image domain and require no explicit 3D construction. Our shape model enables accurate estimation of structure despite segmentation errors or missing views in the input silhouettes, and works even with only a single input view. Using a dataset of thousands of pedestrian images generated from a synthetic model, we can perform accurate inference of the 3D locations of 19 joints on the body based on observed silhouette contours from real images.

Surface Perception from Local Analysis of Texture and Contour

The visual analysis of surface shape from texture and surface contour is treated within a computational framework. The aim of this study is to determine valid constraints that are sufficient to allow surface orientation and distance (up to a multiplicative constant) to be computed from the image of surface texture and of surface contours.

Improving ICP with Easy Implementation for Free Form Surface Matching

Liu, Yonghuai. Improving ICP with Easy Implementation for Free Form Surface Matching. Pattern Recognition, vol. 37, no. 2, pp. 211-226, 2004.

ImageRover: A Content-Based Image Browser for the World Wide Web

ImageRover is a search by image content navigation tool for the world wide web. To gather images expediently, the image collection subsystem utilizes a distributed fleet of WWW robots running on different computers. The image robots gather information about the images they find, computing the appropriate image decompositions and indices, and store this extracted information in vector form for searches based on image content. At search time, users can iteratively guide the search through the selection of relevant examples. Search performance is made efficient through the use of an approximate, optimized k-d tree algorithm. The system employs a novel relevance feedback algorithm that selects the distance metrics appropriate for a particular query.

Image Digestion and Relevance Feedback in the ImageRover WWW Search Engine

ImageRover is a search by image content navigation tool for the world wide web. The staggering size of the WWW dictates certain strategies and algorithms for image collection, digestion, indexing, and user interface. This paper describes two key components of the ImageRover strategy: image digestion and relevance feedback. Image digestion occurs during image collection; robots digest the images they find, computing image decompositions and indices, and storing this extracted information in vector form for searches based on image content. Relevance feedback occurs during index search; users can iteratively guide the search through the selection of relevant examples. ImageRover employs a novel relevance feedback algorithm to determine the weighted combination of image similarity metrics appropriate for a particular query. ImageRover is available and running on the web site.

Estimating 3D Body Pose Using Uncalibrated Cameras

An approach for estimating 3D body pose from multiple, uncalibrated views is proposed. First, a mapping from image features to 2D body joint locations is computed using a statistical framework that yields a set of several body pose hypotheses. The concept of a "virtual camera" is introduced that makes this mapping invariant to translation, image-plane rotation, and scaling of the input. As a consequence, the calibration matrices (intrinsics) of the virtual cameras can be considered completely known, and their poses are known up to a single angular displacement parameter. Given pose hypotheses obtained in the multiple virtual camera views, the recovery of 3D body pose and camera relative orientations is formulated as a stochastic optimization problem. An Expectation-Maximization algorithm is derived that can obtain the locally most likely (self-consistent) combination of body pose hypotheses. Performance of the approach is evaluated with synthetic sequences as well as real video sequences of human motion.

Combining Textual and Visual Cues for Content-based Image Retrieval on the World Wide Web

Some WWW image engines allow the user to form a query in terms of text keywords. To build the image index, keywords are extracted heuristically from HTML documents containing each image, and/or from the image URL and file headers. Unfortunately, text-based image engines have merely retro-fitted standard SQL database query methods, and it is difficult to include images cues within such a framework. On the other hand, visual statistics (e.g., color histograms) are often insufficient for helping users find desired images in a vast WWW index. By truly unifying textual and visual statistics, one would expect to get better results than either used separately. In this paper, we propose an approach that allows the combination of visual statistics with textual statistics in the vector space representation commonly used in query by image content systems. Text statistics are captured in vector form using latent semantic indexing (LSI). The LSI index for an HTML document is then associated with each of the images contained therein. Visual statistics (e.g., color, orientedness) are also computed for each image. The LSI and visual statistic vectors are then combined into a single index vector that can be used for content-based search of the resulting image database. By using an integrated approach, we are able to take advantage of possible statistical couplings between the topic of the document (latent semantic content) and the contents of images (visual statistics). This allows improved performance in conducting content-based search. This approach has been implemented in a WWW image search engine prototype.

Inferring Body Pose without Tracking Body Parts

A novel approach for estimating articulated body posture and motion from monocular video sequences is proposed. Human pose is defined as the instantaneous two dimensional configuration (i.e., the projection onto the image plane) of a single articulated body in terms of the position of a predetermined set of joints. First, statistical segmentation of the human bodies from the background is performed and low-level visual features are found given the segmented body shape. The goal is to be able to map these, generally low level, visual features to body configurations. The system estimates different mappings, each one with a specific cluster in the visual feature space. Given a set of body motion sequences for training, unsupervised clustering is obtained via the Expectation Maximation algorithm. Then, for each of the clusters, a function is estimated to build the mapping between low-level features to 3D pose. Currently this mapping is modeled by a neural network. Given new visual features, a mapping from each cluster is performed to yield a set of possible poses. From this set, the system selects the most likely pose given the learned probability distribution and the visual feature similarity between hypothesis and input. Performance of the proposed approach is characterized using a new set of known body postures, showing promising results.

Articulated Pose Estimation in a Learned Smooth Space of Feasible Solutions

A learning based framework is proposed for estimating human body pose from a single image. Given a differentiable function that maps from pose space to image feature space, the goal is to invert the process: estimate the pose given only image features. The inversion is an ill-posed problem as the inverse mapping is a one to many process. Hence multiple solutions exist, and it is desirable to restrict the solution space to a smaller subset of feasible solutions. For example, not all human body poses are feasible due to anthropometric constraints. Since the space of feasible solutions may not admit a closed form description, the proposed framework seeks to exploit machine learning techniques to learn an approximation that is smoothly parameterized over such a space. One such technique is Gaussian Process Latent Variable Modelling. Scaled conjugate gradient is then used find the best matching pose in the space of feasible solutions when given an input image. The formulation allows easy incorporation of various constraints, e.g. temporal consistency and anthropometric constraints. The performance of the proposed approach is evaluated in the task of upper-body pose estimation from silhouettes and compared with the Specialized Mapping Architecture. The estimation accuracy of the Specialized Mapping Architecture is at least one standard deviation worse than the proposed approach in the experiments with synthetic data. In experiments with real video of humans performing gestures, the proposed approach produces qualitatively better estimation results.