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作者： Parikh, Devi Zitnick, C. Lawrence United States Microsoft Research Redmond United States

ISBN: (纸本)9781457703942

Detecting people remains a popular and challenging problem in computer vision. In this paper, we analyze parts-based models for person detection to determine which components of their pipeline could benefit the most if improved. We accomplish this task by studying numerous detectors formed from combinations of components performed by human subjects and machines. The parts-based model we study can be roughly broken into four components: feature detection, part detection, spatial part scoring and contextual reasoning including non-maximal suppression. Our experiments conclude that part detection is the weakest link for challenging person detection datasets. Non-maximal suppression and context can also significantly boost performance. However, the use of human or machine spatial models does not significantly or consistently affect detection accuracy. © 2011 IEEE.

关键词： computer vision

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The importance of intermediate representations for the modeling of 2D shape detection: Endstopping and curvature tuned computations

The importance of intermediate representations for the model...

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作者： Rodríguez-Sánchez, Antonio J. Tsotsos, John K. Centre for Vision Research Dept. of Computer Science and Engineering York University Toronto ON M3J 1P3 Canada

ISBN: (纸本)9781457703942

Computational models of visual processes with biological inspiration - and even biological realism - are currently of great interest in the computer vision community. This paper provides a biologically plausible model of 2D shape which incorporates intermediate layers of visual representation that have not previously been fully explored. We propose that endstopping and curvature cells are of great importance for shape selectivity and show how their combination can lead to shape selective neurons. This shape representation model provides a highly accurate fit with neural data from [17] and provides comparable results with real-world images to current computer vision systems. The conclusion is that such intermediate representations may no longer require a learning approach as a bridge between early representations based on Gabor or Difference of Gaussian filters (that are not learned since they are well-understood) and later representations closer to object representations that still can benefit from a learning methodology. © 2011 IEEE.

关键词： computer vision

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A boundary-line method for pattern recognition on real particles

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POWDER TECHNOLOGY 2011年第1-3期213卷 155-161页

作者： Liang, Chen Gao, Derek Hubert, Mario Yin, Xiaotian Gao, Chao Bristol Myers Squibb Co New Brunswick NJ 08901 USA Koosur Technol Fremont CA 94538 USA Columbia Univ New York NY 10027 USA NYU Polytech Inst New York NY 11204 USA

In this paper, an algorithm based on boundary-line analysis is developed for the first time to directly recognize polygon shapes with or without concaved angles and without any pre-stored shape templates. The algorithm is also capable of quantitatively characterizing an irregular shape by calculating a similarity number between the subject shape and a comparison polygon shape that is automatically constructed based on the subject shape features. The algorithm first generates an r-L curve from the shape boundary line by plotting the distance (r) between a point on the shape boundary line and the shape center as a function of accumulated boundary length (L). The algorithm then performs first and second derivatives on the r-L curve to find all peak/valley positions, peak-to-peak and peak-to-valley distances. Thus, our algorithm can directly recognize a polygon shape, since the number of peaks equals the number of polygon sides and a peak-to-peak distance equals a polygon side length. In addition, the peak height defines the side's relative orientation if there is no valley corresponding to a concaved angle on the shape. If some valleys are at concaved angles, the number of polygon sides equals the number of peaks plus the number of valleys at concaved angles, and the polygon side length equals the peak-to-valley distance for the valley at a concaved angle. Our algorithm identifies convex/concave angles based on the positive or negative value of the bend angle at the valley point. The algorithm is tested satisfactorily using idealized polygons and real particles of salt, sugar and pharmaceutical powders. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Algorithm computer vision Geometry shape pattern recognition Particle size

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Mental State and Behavior Inference using Mirror Neuron System Architecture for Traffic/Driver Monitoring

Mental State and Behavior Inference using Mirror Neuron Syst...

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IEEE Intelligent Vehicles Symposium (IV)

作者： Varadarajan, Karthik Mahesh Zhou, Kai Vincze, Markus Vienna Univ Technol Vienna Austria

ISBN: (纸本)9781457708916

Traffic psychology presents interesting avenues towards the development of Intelligent Transportation Systems (ITS). Analysis of driver state, emotion and behavior are important components of traffic psychology. While being comprehensive in terms of theoretical frameworks, these analyses lack neurobiological computational models for evaluation. In this paper, we develop computational models for driver state and behavior, also known as Mental State Inference (MSI) based on the Mirror Neuron System (MNS) architecture. The integrated system combines neurobiological models with computer vision techniques for traffic monitoring from surveillance video leading to MSI and event recognition. Evaluation of the system is carried out in terms of actual, psychophysical as well as neurobiological criteria on both simulated and real data. Results demonstrate event and mental state recognition convergence within 0.5 normalized time units for the designed event models on synthetic and real data. The model is also robust to perturbations and is aligned to behavior expected at the psychophysical level.

关键词： Mental status Mirror Neurons Computational modeling Unit of time traffic monitoring computer vision Psychology pattern Evaluation

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On approach to vision based fire detection based on type-2 fuzzy clustering

On approach to vision based fire detection based on type-2 f...

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2011 International Conference of Soft Computing and pattern recognition, SoCPaR 2011

作者： Duong, Ha Dai Nguyen, Dinh Dung Ngo, Long Thanh Tinh, Dao Thanh Department of Information Systems Faculty of Information Technology Le Quy Don Technical University Hanoi Viet Nam

ISBN: (纸本)9781457711947

During the last ten years computer vision techniques have shown a great potential in solving the problem of automatic fire detection. vision-based fire detection offers many advantages over the conventional methods that use smoke and heat detectors. This paper presents a novel approach for fire detection by modeling the structure of spatial of fire, this structure is considered in terms of the color intensity of fire pixels. Furthers the type-2 fuzzy clustering technique is applied to separate fire-color pixels into some clusters, then these clusters are used to model structure of fire. Experimental results show that our method is capable of detecting fire in early state of fire and weak light-intensity environment;and this method uses only information on a single image so it can be integrated into the surveillance system that used dynamic camera. © 2011 IEEE.

关键词： Fuzzy clustering

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Rotation, scaling, and translation resilient watermarking for images

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IET IMAGE PROCESSING 2011年第4期5卷 328-340页

作者： Lin, Y. -T. Huang, C. -Y. Lee, G. C. Natl Chi Nan Univ Inst Curriculum Instruct & Technol Nantou City Taiwan Natl Taiwan Normal Univ Dept Comp Sci & Informat Engn Taipei Taiwan

Traditional watermarking schemes are sensitive to geometric distortions, in which synchronisation for recovering embedded information is a challenging task because of the disorder caused by rotation, scaling or translation (RST). The existing RST-resistant watermarking methods still have limitations with respect to robustness, capacity or fidelity. In this study, the authors address several major problems in RST-invariant watermarking. The first point is how to take advantage of the high RST resilience of scale-invariant feature transform (SIFT) features, which show good performance in terms of RST-resistant pattern recognition. Since many keypoint-based watermarking methods do not discuss cropping attacks, the second issue discussed in this study is how to resist cropping using a human visual system (HVS), which also helps us to eliminate computational complexity. The third issue is the investigation of an HVS-based watermarking strategy for extracting only feature points in the human attentive area. Lastly, a variable-length watermark synchronisation algorithm using dynamic programming is proposed. Experimental results show that the proposed algorithms are practical and show superior performance in comparison with many existing works in terms of watermark capacity, watermark transparency, and the resistance to RST attacks.

关键词： HVS Optimisation techniques Image recognition computer vision and image processing techniques image watermarking Image and video coding image coding synchronisation Mathematical analysis dynamic programming scale-invariant feature transform frequency-domain algorithms SIFT algorithm watermarking feature extraction human visual system frequency-domain analysis pattern recognition Data security spatial-domain algorithms

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A surveillance video analysis and storage scheme for scalable synopsis browsing

A surveillance video analysis and storage scheme for scalabl...

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2011 IEEE International Conference on computer vision Workshops, ICCV Workshops 2011

作者： Wang, Shizheng Yang, Jianwei Zhao, Yanyun Cai, Anni Stan, Z. CBSR and NLPR Institute of Automation Chinese Academy of Sciences China Multimedia Communication and Pattern Recognition Labs Beijing University of Posts and Telecommunications China

ISBN: (纸本)9781467300629

We propose a framework for efficient storing and scalable browsing of surveillance video based on video synopsis. Our framework employs a novel synopsis analysis scheme named Detail-based video synopsis to generate a set of object flags to store and browse surveillance video synopsis. The main contributions of our work are: 1) highlighting important contents of surveillance video;2) improving the storage efficiency of original video and synopsis video;3) realizing multi-scale scalable browsing of synopsis video while reserving essential information. The experiments of implementing the framework are shown compared with the previous independent storage method of original video and synopsis video. © 2011 IEEE.

关键词： Monitoring

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A probabilistic representation for efficient large scale visual recognition tasks

A probabilistic representation for efficient large scale vis...

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作者： Bhattacharya, Subhabrata Sukthankar, Rahul Jin, Rong Shah, Mubarak Intel Labs Carnegie Mellon University Pittsburgh PA United States Michigan State University East Lansing MI United States Computer Vision Lab University of Central Florida Orlando FL United States

ISBN: (纸本)9781457703942

In this paper, we present an efficient alternative to the traditional vocabulary based on bag-of-visual words (BoW) used for visual classification tasks. Our representation is both conceptually and computationally superior to the bag-of-visual words: (1) We iteratively generate a Maximum Likelihood estimate of an image given a set of characteristic features in contrast to the BoW methods where an image is represented as a histogram of visual words, (2) We randomly sample a set of characteristic features instead of employing computation-intensive clustering algorithms used during the vocabulary generation step of BoW methods. Our performance compares favorably to the state-of-the-art on experiments over three challenging human action and a scene categorization dataset, demonstrating the universal applicability of our method. © 2011 IEEE.

关键词： Clustering algorithms

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Inspection and grading of surface defects of fruits by computer vision

Inspection and grading of surface defects of fruits by compu...

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International Conference on Advanced Design and Manufacturing Engineering (ADME 2011)

作者： Li, Jiangbo Rao, Xiuqin Ying, Yibin Zhejiang Univ Coll Biosyst Engn & Food Sci Hangzhou 310058 Zhejiang Peoples R China

ISBN: (纸本)9783037852163

computer vision is a rapid, consistent and objective inspection technique, which has expanded into many diverse industries. Its speed and accuracy provide one alternative for an automated, non-destructive and cost-effective technique to accomplish ever-increasing production and quality requirements. This method of inspection has found applications in the agricultural industry, including the inspection and grading of fruits. This paper provides an introduction to main defection and grading approaches of fruit external defects, including image processing and pattern recognition methods based on fruit two-dimensional (2D) and three-dimensional (3D) information, and hyperspectral and multispectral imaging. In addition, their advantages and disadvantages are also discussed.

关键词： Fruits Machine vision Colour imaging Monochrome imaging Fluorescence imaging Hyperspectral imaging multispectral imaging External defects Inspection Grading

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A biologically inspired memory in a multi-agent based robotic architecture

A biologically inspired memory in a multi-agent based roboti...

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23rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI)

作者： Arredondo, Tomas Castillo, Patricio Benapres, Pablo Quiroz, Javiera Torres, Miguel Univ Tecn Federico Santa Maria Dept Elect Engn Valparaiso Chile Pontificia Univ Catolica Chile Dept Elect Engn Santiago Chile

ISBN: (纸本)9780769545967

We describe a biologically inspired memory in a multi-agent based robotic architecture. In this approach, memory and pattern recognition are intertwined to form a cognitive memory that is used for recognition of objects in a robotics environment. This memory is implemented in a multiple agent behavior based blackboard architecture as an object recognition agent. The agent performance is tested against a standard dataset with satisfactory results. The system is currently installed in a mobile robotic platform where its capabilities and applications are explored.

关键词： Biology computer architecture Image segmentation Machine vision pattern recognition Robots Training architecture biological biologically inspired memory blackboard blackboard architecture cognitive cognitive memory cognitive systems memory mobile robotic

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