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6th IAPR Workshop on Pattern Recognition in Remote Sensing, PRRS 2010

作者： Cetin, Melih Halici, Ugur Aytekin, Örsan Computer Vision and Intelligent Systems Research Laboratory Dept. of Electrical and Electronics Eng. Middle East Technical University Turkey

ISBN: (纸本)9781424472574

A method based on textural features and Adaboost for detecting buildings in satellite images is proposed. Several local textural features including mean and standard deviation of image intensity and gradient, Zernike moments, Circular-Mellin features, Haralick features, Fourier Power Spectrum, Wavelets, Gabor Filters, and a set features extracted from HSV color space are extracted. Adaboost learning algorithm is employed for both classification and determining the beneficial feature subset, due to its feature selector nature. Some operation including morphological operators are applied for post processing. The approach was tested on a set of satellite images having different types of buildings and promising experimental results are achieved. © 2010 IEEE.

关键词： Adaptive boosting

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Interest point based tracking

Interest point based tracking

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2010 20th International Conference on Pattern Recognition, ICPR 2010

作者： Kloihofer, Werner Kampel, Martin Research and Development Image Processing Center Communication Systems GmbH Vienna Austria Computer Vision Lab. Vienna University of Technology Vienna Austria

ISBN: (纸本)9780769541099

This paper deals with a novel method for object tracking. In the first step interest points are detected and feature descriptors around them are calculated. Sets of known points are created, allowing tracking based on point matching. The set representation is updated online at every tracking step. Our method uses one-shot learning with the first frame, so no offline and no supervised learning is required. Following an object recognition based approach there is no need for a background model or motion model, allowing tracking of abrupt motion and with non-stationary cameras. We compare our method to MeanShift and Tracking via Online Boosting, showing the benefits of our approach. © 2010 IEEE.

关键词： Object detection

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MULTI-CAMERA POSITIONING FOR AUTOMATED TRACKING systems IN DYNAMIC ENVIRONMENTS

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International Journal of Information Acquisition 2010年第3期7卷 225-242页

作者： YI YAO CHUNG-HAO CHEN BESMA ABIDI DAVID PAGE ANDREAS KOSCHAN MONGI ABIDI Visualization and Computer Vision Lab GE Global Research USA Department of Mathematics and Computer Science North Carolina Central University USA Imaging Robotics and Intelligent Systems Lab University of Tennessee Knoxville USA

Most existing camera placement algorithms focus on coverage and/or visibility analysis, which ensures that the object of interest is visible in the camera's field of view (FOV). According to recent literature, handoff safety margin is introduced to sensor planning so that sufficient overlapped FOVs among adjacent cameras are reserved for successful and smooth target transition. In this paper, we investigate the sensor planning problem when considering the dynamic interactions between moving targets and observing cameras. The probability of camera overload is explored to model the aforementioned interactions. The introduction of the probability of camera overload also considers the limitation that a given camera can simultaneously monitor or track a fixed number of targets and incorporates the target's dynamics into sensor planning. The resulting camera placement not only achieves the optimal balance between coverage and handoff success rate but also maintains the optimal balance in environments with various target densities. The proposed camera placement method is compared with a reference algorithm by Erdem and Sclaroff. Consistently improved handoff success rate is illustrated via experiments using typical office floor plans with various target densities.

关键词： Sensor planning visual surveillance multiple camera systems camera handoff

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Sonify your face: Facial expressions for sound generation

Sonify your face: Facial expressions for sound generation

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18th ACM International Conference on Multimedia ACM Multimedia 2010, MM'10

作者： Valenti, Roberto Jaimes, Alejandro Sebe, Nicu Intelligent Systems Lab. Amsterdam University of Amsterdam Netherlands Yahoo Research Barcelona Spain Department of Information Engineering and Computer Science University of Trento Italy

ISBN: (纸本)9781605589336

We present a novel visual creativity tool that automatically recognizes facial expressions and tracks facial muscle movements in real time to produce sounds. The facial expression recognition module detects and tracks a face and outputs a feature vector of motions of specific locations in the face. The feature vector is used as input to a Bayesian network which classifies facial expressions into several categories (e.g., angry, disgusted, happy, etc.). The classification results are used along with the feature vector to generate a combination of sounds that change in real time depending on the person's facial expressions. We explain the artistic motivation behind the work, the basic components of our tool, and possible applications in the arts (performance, installation) and in the medical domain. Finally, we report on the experience of approximately 25 users of our system at a conference demonstration session, of 9 participants in a pilot study to assess the system's usability, and discuss our experience installing the work at an important digital arts festival (RE-NEW 2009). © 2010 ACM.

关键词： Bayesian networks

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Fast shape matching and retrieval based on approximate dynamic space warping

Fast shape matching and retrieval based on approximate dynam...

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15th International Symposium on Artificial Life and Robotics, AROB '10

作者： Alajlan, Naif Advanced Lab. for Intelligent Systems Research Department of Computer Engineering King Saud University P.O.Box 51178 Riyadh 11543 Saudi Arabia

ISBN: (纸本)9784990288044

Dynamic space warping (DSW) has emerged as a very effective tool for matching shapes. However, a central computational difficulty associated with DSW arises when a boundary's starting point (or rotation angle) is unknown. In this paper, the HopDSW algorithm is proposed to speed up the starting point computation. Rather than performing an exhaustive search for the correct starting point as in classical approaches, the proposed algorithm operates in a coarse-to-fine manner. The coarse search is global and uses a hopping step to exclude points from the search. Then, the search is refined in the neighborhood of the solution of the coarse search. A criterion that governs selecting the hopping step parameter is given, which reduces the number of starting point computations by an order. For shape representation, triangle area signature (TAS) is computed from triangles formed by the boundary points. Experimental results on the MPEG-7 CE-1 database of 1400 shapes show that the proposed algorithm returns the solution of the exhaustive search with a high degree of accuracy and a considerable reduction in the number of computations. © 2010 ISAROB.

关键词： Dynamic programming

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A model-driven classification and recursive segmentation method for automatic panel extraction from biological and medical papers

A model-driven classification and recursive segmentation met...

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IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)

作者： Xiaohui Yuan Dongyu Ang Computer Vision and Intelligent Systems Lab Department of CSE University of North Texas Denton TX USA

We present a novel method to automatically extract panels from figures in biomedical articles. Our method consists of figure (or panel) classification and panel segmentation. Figure classification determines the existence of photograph in a figure. A Gaussian model is constructed for photographs and plots. Figures and panels are evaluated based on the model to determine their class. If it contains photographs, an iterative panel-splitting process follows. This process continues until no further straight lines are identified in the subfigures. Experiments were conducted with 182 figures from 25 articles published in different journals. Despite vast difference between figures, our method successfully extracted both plots and photographs and was able to identify zoom-in views that are superimposed on the original photographs.

关键词： Histograms Image segmentation Pixel Biomedical imaging Data mining Biology Transforms

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Cost-optimal planning using weighted MaxSAT

Cost-optimal planning using weighted MaxSAT

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Workshop on Constraint Satisfaction Techniques for Planning and Scheduling Problems, COPLAS 2010

作者： Robinson, Nathan Gretton, Charles Pham, Duc-Nghia Sattar, Abdul ATOMIC Project Queensland Research Lab. NICTA QLD Australia Institute for Integrated and Intelligent Systems Griffith University QLD Australia School of Computer Science University of Birmingham United Kingdom

We consider the problem of computing optimal plans for propositional planning problems with action costs. In the spirit of leveraging advances in general-purpose automated reasoning for that setting, we develop an approach that operates by solving a sequence of partial weighted MaxSAT problems, each of which corresponds to a step-bounded variant of the problem at hand. Our approach is the first SAT-based system in which a proof of cost optimality is obtained using a MaxSAT procedure. It is also the first system of this kind to incorporate an admissible planning heuristic. We perform a detailed empirical evaluation of our work using benchmarks from a number of International Planning Competitions.

关键词： Costs

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Building detection in satellite images by textural features and Adaboost

Building detection in satellite images by textural features ...

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IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS)

作者： Melih Cetin Ugur Halici Örsan Aytekin Computer Vision and Intelligent Systems Research Laboratory Department of Electrical and Electronics Engineering Middle East Technical University Turkey

关键词： Buildings Feature extraction Pixel Satellites Classification algorithms Remote sensing Image color analysis

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Watershed-based weighted graph partitioning active contours

Watershed-based weighted graph partitioning active contours

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2010 3rd International Congress on Image and Signal Processing, CISP 2010

作者： Wang, Shaorong Chen, Yisong Li, Sheng Wang, Guoping Li, Hua Key Lab. of Machine Perception and Intelligent MOE Beijing 100871 China HCI and Multimedia Lab. Dept. of Computer Science Peking University Beijing 100871 China National Research Center for Intelligent Computing Systems Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China

A novel Weighted Graph Partitioning Active Contours method based on weighted dissimilarity is introduced. This method is easy to be extended by defining different types of similarities. And it has been greatly acceler... 详细信息

ISBN: (纸本)9781424465149

关键词： Image segmentation

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Geographic information for vision-based road detection

Geographic information for vision-based road detection

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IEEE Symposium on intelligent Vehicle

作者： José M. Alvarez Felipe Lumbreras Theo Gevers Antonio M. López Computer Vision Center and Computer Science Dpt. Univ. Autonoma de Barcelona Spain Intelligent Systems Lab Amsterdam University of Amsterdam and Comp. Vision Center Barcelona Spain

Road detection is a vital task for the development of autonomous vehicles. The knowledge of the free road surface ahead of the target vehicle can be used for autonomous driving, road departure warning, as well as to support advanced driver assistance systems like vehicle or pedestrian detection. Using vision to detect the road has several advantages in front of other sensors: richness of features, easy integration, low cost or low power consumption. Common vision-based road detection approaches use low-level features (such as color or texture) as visual cues to group pixels exhibiting similar properties. However, it is difficult to foresee a perfect clustering algorithm since roads are in outdoor scenarios being imaged from a mobile platform. In this paper, we propose a novel high-level approach to vision-based road detection based on geographical information. The key idea of the algorithm is exploiting geographical information to provide a rough detection of the road. Then, this segmentation is refined at low-level using color information to provide the final result. The results presented show the validity of our approach.

关键词： Vehicle detection Remotely operated vehicles Road vehicles Mobile robots Vehicle driving Clustering algorithms Sensor phenomena and characterization Costs Energy consumption Image segmentation

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