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2nd International Symposium on Brain, vision and Artificial Intelligence

作者： Radilova, Jirina Taddei-Ferretti, Cloe Musio, Carlo Santillo, Silvia Cibelli, Edoardo Cotugno, Antonio Radil, Tomas CAS Inst Physiol Prague Czech Republic CNR Ist Cibernetica Eduardo Caianiello I-00185 Rome Italy Ist Filosofia PFTIM SL Naples Italy

Spontaneous figure reversal of ambiguous patterns was analyzed in humans by presenting "Necker-cube"-fike, or "drum"-like figures having square or round shaped "front" and "rear"... 详细信息

ISBN: (纸本)9783540755548

Spontaneous figure reversal of ambiguous patterns was analyzed in humans by presenting "Necker-cube"-fike, or "drum"-like figures having square or round shaped "front" and "rear" surfaces, and either large or small "depth". The figures were perceived alternately according to one or the other of two possible mental orientation-interpretations. The subjects signalled the instant of subjective pattern-reversals. Results: perceptual intervals corresponding to both interpretations of "drum" were longer than those of "cube";the perceived "depth" of the figures was less relevant for reversal timing ("deeper" figures reversed only slightly more slowly and the corresponding intervals were somewhat longer). Although the shape of "front" and "rear" surfaces was not a crucial geometrical feature for representing the three-dimensional nature of the patterns on the two-dimensional stimulus plane, it markedly influenced the timing of figure reversals. More, or longer information processing steps should needed for perceptual -cogn i tive representations of curvilinear patterns in comparison with rectangular ones.

关键词： ambiguous pattern reversal Necker cube information processing steps object recognition mental interpretation

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A comparision of Model-based methods for knee cartilage segmentation

A comparision of Model-based methods for knee cartilage segm...

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2nd International Conference on computer vision Theory and Applications, VISAPP 2007

作者： Cheong, J. Faggian, N. Langs, G. Suter, D. Cicuttini, F. Dept. of Electrical Dept. of Computer Systems Engineering Monash University Australia Clayton School of Information Technology Monash University Australia Institute for Computer Graphics and Vision Graz University of Technology Austria Pattern Recognition and Image Processing Group Vienna University of Technology Austria Dept. of Epidemiology Dept. of Preventive Medicine Monash University Australia

Osteoarthritis is a chronic and crippling disease affecting an increasing number of people each year. With no known cure, it is expected to reach epidemic proportions in the near future. Accurate segmentation of knee cartilage from magnetic resonance imaging (MRI) scans facilitates the measurement of cartilage volume present in a patient's knee, thus enabling medical clinicians to detect the onset of osteoarthritis and also crucially, to study its effects. This paper compares four model-based segmentation methods popular for medical data segmentation, namely Active Shape Models (ASM) (Cootes et al., 1995), Active Appearance Models (AAM) (Cootes et al., 2001), Patch-based Active Appearance Models (PAAM) (Faggian et al., 2006), and Active Feature Models (AFM) (Langs et al., 2006). A comprehensive analysis of how accurately these methods segment human tibial cartilage is presented. The results obtained were benchmarked against the current "gold standard" (cartilage segmented manually by trained clinicians) and indicate that modeling local texture features around each landmark provides the best results for segmenting human tibial cartilage.

关键词： Medical imaging

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Protein structure-structure alignment with discrete frechet distance

Protein structure-structure alignment with discrete frechet ...

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5th Asia-Pacific Bioinformatics Conference (APBC2007)

作者： Jiang, Minghui Xu, Ying Zhu, Binhai Utah State Univ Dept Comp Sci Logan UT 84322 USA Univ Georgia Dept Biochem & Mol Biol Athens GA 30602 USA Montana State Univ Dept Comp Sci Bozeman MT 59717 USA

ISBN: (纸本)9781860947834

Matching two geometric objects in 2D and 3D spaces is a central problem in computer vision, pattern recognition and protein structure prediction. In particular, the problem of aligning two polygonal chains under translation and rotation to minimize their distance has been studied using various distance measures. It is well known that the Hausdorff distance is useful for matching two point sets, and that the Frechet distance is a superior measure for matching two polygonal chains. The discrete Frechet distance closely approximates the (continuous) Frechet distance,and is a natural measure for the geometric similarity of the folded 3D structures of bio-molecules such as proteins. In this paper, we present new algorithms for matching two polygonal chains in 2D to minimize their discrete Frechet distance under translation and rotation, and an effective heuristic for matching two polygonal chains in 3D. We also describe our empirical results on the application of the discrete Frechet distance to the protein structure-structure alignment.

关键词： pattern recognition

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Learning the lie groups of visual invariance

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NEURAL COMPUTATION 2007年第10期19卷 2665-2693页

作者： Miao, Xu Rao, Rajesh P. N. Univ Washington Dept Comp Sci & Engn Seattle WA 98195 USA

A fundamental problem in biological and machine vision is visual invariance: How are objects perceived to be the same despite transformations such as translations, rotations, and scaling? In this letter, we describe a new, unsupervised approach to learning invariances based on Lie group theory. Unlike traditional approaches that sacrifice information about transformations to achieve invariance, the Lie group approach explicitly models the effects of transformations in images. As a result, estimates of transformations are available for other purposes, such as pose estimation and visuomotor control. Previous approaches based on first-order Taylor series expansions of images can be regarded as special cases of the Lie group approach, which utilizes a matrix-exponential-based generative model of images and can handle arbitrarily large transformations. We present an unsupervised expectation-maximization algorithm for learning Lie transformation operators directly from image data containing examples of transformations. Our experimental results show that the Lie operators learned by the algorithm from an artificial data set containing six types of affine transformations closely match the analytically predicted affine operators. We then demonstrate that the algorithm can also recover novel transformation operators from natural image sequences. We conclude by showing that the learned operators can be used to both generate and estimate transformations in images, thereby providing a basis for achieving visual invariance.

关键词： computer vision pattern recognition systems ARTIFICIAL intelligence IMAGE processing EXPECTATION-maximization algorithms LIE algebras LIE groups

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Human activity recognition and pathological gait pattern identification

Human activity recognition and pathological gait pattern ide...

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作者： Niu, Feng University of Miami

学位级别：Ph.D.

Human activity analysis has attracted great interest from computer vision researchers due to its promising applications in many areas such as automated visual surveillance, computer-human interactions, and motion-based identification and diagnosis. This dissertation presents work in two areas: general human activity recognition from video, and human activity analysis for the purpose of identifying pathological gait from both 3D captured data and from video. Even though the research in human activity recognition has been going on for many years, still there are many issues that need more research. This includes the effective representation and modeling of human activities and the segmentation of sequences of continuous activities. In this thesis we present an algorithm that combines shape and motion features to represent human activities. In order to handle the activity recognition from any viewing angle we quantize the viewing direction and build a set of Hidden Markov Models (HMMs), where each model represents the activity from a given view. Finally, a voting based algorithm is used to segment and recognize a sequence of human activities from video. Our method of representing activities has good attributes and is suitable for both low resolution and high resolution video. The voting based algorithm performs the segmentation and recognition simultaneously. Experiments on two sets of video clips of different activities show that our method is effective. Our work on identifying pathological gait is based on the assumption of gait symmetry. Previous work on gait analysis measures the symmetry of gait based on Ground Reaction Force data, stance time, swing time or step length. Since the trajectories of the body parts contain information about the whole body movement, we measure the symmetry of the gait based on the trajectories of the body parts. Two algorithms, which can work with different data sources, are presented. The first algorithm works on 3D motion-captured da

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Quality assessment of beef based of computer vision and electronic nose

Quality assessment of beef based of computer vision and elec...

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8th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing/3rd ACIS International Workshop on Self-Assembling Wireless Networks

作者： Chen Cunshe Li Xiaojuan Yuan Huimei Beijing Technol & Business Univ Sch Chem & Environm Engn Beijing 100037 Peoples R China Capital Normal Univ Informat Engn Coll Beijing 100101 Peoples R China

ISBN: (纸本)0769529097

Current techniques for beef quality evaluations rely on sensory methods. These procedures are subjective, prone to error, and difficult to quantify. Automated evaluation of color and odor is desirable to reduce subjectivity and discrepancies and assist with the creation of standards for inspectors worldwide. The objectives of this study were to develop color machine vision techniques for visual evaluation and to test electronic nose sensors for odor raw and beef. A color machine vision system was developed to analyze the color of beef samples. The system was able to analyze the color of samples with non-uniform color surfaces, An electronic nose sensors was used to measure odors of beef and beef stored at different temperatures, with different levels of spoilage. Discriminant function analysis was used as the pattern recognition technique to differentiate samples based on odors. Results showed that the electronic nose could discriminate differences in odor due to storage time and spoilage levels for beef. Results also showed good correlation of sensor reading with sensory scores Overall. the electronic nose showed good sensitivity and accuracy. Results from this work could lead to methodologies that will assist in the objective and repeatable quality evaluation of beef. These methods have potential in industrial and regulatory application where rapid response, no sample preparation, and no need for chemicals are required.

关键词： computer vision electronic nose beef

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Synchronization of video sequences from free-moving cameras

Synchronization of video sequences from free-moving cameras

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3rd Iberian Conference on pattern recognition and Image Analysis, IbPRIA 2007

作者： Serrat, Joan Diego, Ferran Lumbreras, Felipe Álvarez, José Manuel Computer Vision Center and Computer Science Dept. Edifici O Universitat Autònoma de Barcelona 08193 Cerdanyola Spain

ISBN: (纸本)9783540728481

We present a new method for the synchronization of a pair of video sequences and the spatial registration of all the temporally corresponding frames. This is a mandatory step to perform a pixel wise comparison of a pair of videos. Several proposals for video matching can be found in the literature, with a variety of applications like object detection, visual sensor fusion, high dynamic range and action recognition. The main contribution of our method is that it is free from three common restrictions assumed in previous works. First, it does not impose any condition on the relative position of the two cameras, since they can move freely. Second, it does not assume a parametric temporal mapping relating the time stamps of the two videos, like a constant or linear time shift. Third, it does not rely on the complete trajectories of image features (points or lines) along time, something difficult to obtain automatically in general. We present our results in the context of the comparison of videos captured from a camera mounted on moving vehicles. © Springer-Verlag Berlin Heidelberg 2007.

关键词： Image fusion

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Advances in Brain, vision, and Artificial Intelligence - Second International Symposium, BVAI 2007, Proceedings

Advances in Brain, Vision, and Artificial Intelligence - Sec...

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2nd International Symposium on Brain, vision, and Artificial Intelligence, BVAI 2007

ISBN: (纸本)3540755543

The proceedings contain 58 papers. The topics discussed include: physiology of simple photoreceptors in the abdominal ganglion of onchidium;diffuse nerve net of hydra revealed by NADPH-diaphorase histochemical labeling;on global geometry of image of eye's back;independent encoding of position and orientation by population responses in primary visual cortex;a neural model for attentional modulation of lateral interactions in the visual cortex;higher order color mechanisms for image segmentation;temporal characteristics of artificial retina based on bacteriorhodopsin and its variants;a neural network model for a view independent extraction of reach-to-grasp action features;neuromimetic indicators for visual perception of motion;different binding strategies for the different stages of visual recognition;and a self-organizing approach to detection of moving patterns for real-time applications.

关键词： Image segmentation

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Handwritten bangla compound character recognition using gradient feature

Handwritten bangla compound character recognition using grad...

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10th International Conference on Information Technology, ICIT 2007

作者： Pal, U. Wakabayashi, T. Kimura, F. Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-108 India Graduate School of Engineering Mie University 1577 Kurimamachiya-cho Tsu Mie Japan

ISBN: (纸本)0769530680

recognition of handwritten characters of Indian script is difficult because of the presence of many complex shaped compound characters (cluster characters) as well as variability involved in the writing style of different individuals. This paper deals with recognition of off-line Bangla handwritten compound characters using Modified Quadratic Discriminant Function (MQDF). The features used for recognition purpose are mainly based on directional information obtained from the arc tangent of the gradient. To get the feature, at first, a 2 X 2 mean filtering is applied 4 times on the gray level image and a non-linear size normalization is done on the image. A Roberts filter is then applied on the normalized image to obtain gradient image. Next, the arc tangent of the gradient (direction of gradient) is initially quantized into 32 directions and the strength of the gradient is accumulated with each of the quantized direction. Finally, the frequencies of these directions are down sampled using Gaussian filter to get 392 dimensional feature vectors. Using 5-fold cross validation technique we obtained 85.90% accuracy from a dataset of Bangla compound characters containing 20,543 samples. © 2007 IEEE.

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Sparse MRF appearance models for fast anatomical structure localisation

Sparse MRF appearance models for fast anatomical structure l...

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2007 18th British Machine vision Conference, BMVC 2007

作者： Donner, René Mičušsík, Branislav Langs, Georg Bischof, Horst Institute for Computer Graphics and Vision Graz University of Technology Austria Pattern Recognition and Image Processing Group Vienna University of Technology Austria GALEN Group Laboratoire de Mathématiques Appliquées Aux Systèmes Ecole Centrale de Paris France

ISBN: (纸本)1901725340

Image segmentation methods like active shape models, active appearance models or snakes require an initialisation that guarantees a considerable overlap with the object to be segmented. In this paper we present an approach that localises anatomical structures in a global manner by means of Markov Random Fields (MRF). It does not need initialisation, but finds the most plausible match of the query structure in the image. It provides for precise, reliable and fast detection of the structure and can serve as initialisation for more detailed segmentation steps. Sparse MRF Appearance Models (SAMs) encode a priori information about the geometric configurations of interest points, local features at these points and local features along the edges of adjacent points. This information is used to formulate a Markov Random Field and the mapping of the modeled object (e.g. a sequence of vertebrae) to the query image interest points is performed by the MAX-SUM algorithm. The local image information is captured by novel symmetry-based interest points and local descriptors derived from Gradient Vector Flow. Experimental results are reported for two data-sets showing the applicability to complex medical data.

关键词： Image segmentation

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