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Bridging the Web and Perceptual User Interfaces
No full textWe present a system that bridges the perceptual user interfaces paradigm and web applications, and thus allows us to control a web application through hand-gestures. It exemplifies a general interaction architecture that enables multi-modal interaction for arbitrary, unchanged web applications and thus makes available a large number of real-world applications for multi-modal interaction. In addition, we demonstrate how knowledge about the user interface provides a powerful constraint for pattern analysis. First evaluation results for the approach are given with respect to an image viewing web application
Central Catadioptric Camera Calibration using Planar Objects
Get PDFCentral catadioptric cameras combine lenses with mirrors to enlarge the field of view while keeping a single effective viewpoint. In this paper we propose a novel method of calibrating the intrinsic parameters of central catadioptric cameras using a planar object. Based on the viewing sphere model, we can warp a portion of the catadioptric image to an image captured by a virtual perspective camera with given intrinsic and extrinsic parameters. We show that placing the planar object several times around the catadioptric camera is equivalent to placing the same object at different poses relative to a static virtual perspective camera. Therefore, homography method can be applied to calculate the relative poses of the planar object as well as the projection error of feature points on the planar object. By minimizing the projection error, we can obtain the optimized intrinsic parameters of the central catadioptric camera. Besides simplicity, experiments with simulation and real image data clearly demonstrate the high robustness and accuracy of the proposed calibration method
Dynamic Visual Attention: competitive versus motion priority scheme
Get PDFDefined as attentive process in presence of visual sequences, dynamic visual attention responds to static and motion features as well. For a computer model, a straightforward way to integrate these features is to combine all features in a competitive scheme: the saliency map contains a contribution of each feature, static and motion. Another way of integration is to combine the features in a motion priority scheme: in presence of motion, the saliency map is computed as the motion map, and in absence of motion, as the static map. In this paper, four models are considered: two models based on a competitive scheme and two models based on a motion priority scheme. The models are evaluated experimentally by comparing them with respect to the eye movement patterns of human subjects, while viewing a set of video sequences. Qualitative and quantitative evaluations, performed in the context of simple synthetic video sequences, show the highest performance of the motion priority scheme, compared to the competitive scheme
Easy-to-use calibration of multiple-camera setups
Get PDFCalibration of the pinhole camera model has a well-established theory, especially in the presence of a known calibration object. Unfortunately, in wide-base multi-camera setups, it is hard to create a calibration object, which is visible by all the cameras simultaneously. This results in the fact that conventional calibration methods do not scale well. Using well-known algorithms, we developed a streamlined calibration method, which is able to calibrate multi-camera setups only with the help of a planar calibration object. The object does not have to be observed by at the same time by all the cameras involved in the calibration. Our algorithm breaks down the calibration into four consecutive steps: feature extraction, distortion correction, intrinsic and finally extrinsic calibration. We also made the implementation of the presented method available from our website
Fast Outdoor Robot Localization Using Integral Invariants
Get PDFGlobal Integral Invariant Features have shown to be useful for robot localization in indoor environments. In this paper, we present a method that uses Integral Invariants for outdoor environments. To make the Integral Invariant Features more distinctive for outdoor images, we first split the image into a grid of subimages. Then we calculate integral invariants for each grid cell individually and concatenate the results to get the feature vector for the image. Additionally, we combine this method with a particle filter to improve the localization results. We compare our approach to a Scale Invariant Feature Transform (SIFT)-based approach on images of two outdoor areas and under different illumination conditions. The results show that the SIFT approach is more exact, but the Grid Integral Invariant approach is faster and allows localization in significantly less than one second
How to formulate image processing applications?
Get PDFThis paper presents a system dedicated to the formulation of image processing applications for inexperienced users. We propose models and their formalization through ontologies that identify and organize the necessary and sufficient information to design such applications. We also explain the interaction means we develop to help the user to give a good formulation of the considered image processing problem
Individual Animal Identification using Visual Biometrics on Deformable Coat Patterns
Get PDFIn this paper we propose and evaluate an approach to the so far unsolved problem of robust _individual_ identification of patterned animals based on video filmed in widely unconstrained, natural habitats. Experimental results are presented for a prototype system trained on African penguins operating in a real-world animal colony of thousands. The system exploits the individuality of Turing-like camouflage patterns as identity cues since, for a wide range of species, these contain highly unique and compact distributions of phase singularities. The key problem solved in this paper is a distortion robust detection and individual comparison of non-linearly _deforming_ animals. We address the problem using a coarse-to-fine methodology that task-specifically extends and combines vision techniques in a three-stage approach: 1) Using a recently suggested integration of multiple instances of appearance detectors (Viola-Jones) and sparse feature trackers (Lucas-Kanade), a coarse, robust real-time detection of animals in appropriate poses is achieved. 2) An estimation of the 3D-deformed pose is derived by a fast, guided search on a precalculated pose-configuration model, we refer to as _Feature Prediction Tree_, which is learned off-line based on an animated, deformable 3D species-model. The estimate is refined using bundle adjustment posing a polygonal model into the scene. Following, a back-projection of the visible animal surface yields a normalised 2D texture map. 3) An extended variant of _Shape Context_ descriptors (built from filter-extracted phase singularities of characteristic texture areas) are employed as biometric templates. Finally, a distortion-robust identification is achieved by solving associated bipartite graph matching tasks for pairs of these descriptors
Intelligent modification for the daltonization process of digitized paintings
Get PDFDaltonization is a procedure for adapting colors in an image or a sequence of images for improving the color perception by a color-deficient viewer. In this paper an intelligent/enhanced daltonization method for individuals suffering from protanopia is proposed. The algorithm implements logical image masking in order to modify the colors that are confused and to preserve those colors that are perceived correctly. The proposed method modifies iteratively the parameters for image daltonization after the provision of the initial conditions. The distinctive characteristic of the proposed approach is that when it is combined with a color-checking module, optimum daltonization parameters are effectively identified. Examples are provided in details, as well as screenshots from the algorithm when it is applied in digitized paintings/artworks
Open-Ended Inference of Relational Representations in the COSPAL Perception-Action Architecture
No full textThe COSPAL architecture for autonomous artifical cognition utilises incremental perception-action learning in order to generate hierarchically-grounded abstract representations of an agent's environment on the basis of its action capabilities. We here give an overview of the top-level relational module of this architecture. The first stage of the process hence involves the application of ILP to attempted action outcomes in order to determine the set of generalised rule protocols governing actions within the agent's environment (initially defined via an a priori low-level representation). In the second stage, imposing certain constraints on legitimate first-order logic induction permits a compact reparameterisation of the percept space such that novel perceptual-capabilities are always correlated with novel action capabilites. We thereby define a meaningful empirical criterion for perceptual inference. Novel perceptual capabilities are of a higher abstract order than the a priori environment representation, allowing more sophisticated exploratory action to be taken. Gathering of further exploratory data for rule induction hence takes place in an iterative cycle. Application of this mechanism within a simulated shape-sorter puzzle environment indicates that this approach significantly accelerates learning of the correct environment model
Robust Registration of Long Sport Video Sequence
Get PDFAutomatic registration plays an important role for a sport analysis system, the automation and accuracy of the registration for a long video sequence can still be an open problem for many practical applications. We propose a novel method to cope with it: (1) Reference frames can be introduced as a transaction of computing homography to map each frame of the imagery to the globally consistent model of the rink, that can reduce the accumulative error of successive registration and make the system more automatic. (2) An more distinctive invariant point feature (SIFT) can be used to provide reliable and robust matching across large range of affine distortion and change in illumination, that can improve the computational precision of homography. Experimental results show that the proposed algorithm is very efficient and effective on video recorded live by the authors in the World Short Track Speed Skating Championships