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Natural Scene Classification Inspired by Visual Perception and Cognition Mechanisms

重庆理工大学学报（自然科学） 2011年第7期25卷 24-43页

作者： ZHANG Rui Robotics and Computer Vision Laboratory Dept. of Electrical and Computer Engineering Queen＇ s University Canada

The process of human natural scene categorization consists of two correlated stages: visual perception and visual cognition of natural *** by this fact,we propose a biologically plausible approach for natural scene image *** approach consists of one visual perception model and two visual cognition *** visual perception model,composed of two steps,is used to extract discriminative features from natural scene *** the first step,we mimic the oriented and bandpass properties of human primary visual cortex by a special complex wavelets transform,which can decompose a natural scene image into a series of 2D spatial structure *** the second step,a hybrid statistical feature extraction method is used to generate gist features from those 2D spatial structure *** we design a cognitive feedback model to realize adaptive optimization for the visual perception *** last,we build a multiple semantics based cognition model to imitate human cognitive mode in rapid natural scene *** on natural scene datasets show that the proposed method achieves high efficiency and accuracy for natural scene classification.

关键词： natural scene classification visual perception model visual cognition model

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Surface reconstruction methods for the recovery of 3D models from underwater interest areas

Surface reconstruction methods for the recovery of 3D models...

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OCEANS - Europe

作者： Ricard Campos Rafael Garcia Tudor Nicosevici Computer Vision and Robotics Group University of Girona Spain

3D models of seafloor interest areas having a strong 3D relief are a rich source of information for scientists. In the recent years, the computer vision community has been developing techniques to achieve the discrete reconstruction of these interest areas from a set of images. However, 3D reconstruction methods output a 3D point cloud as a representation of the shape of the observed object/area. This representation lacks connectivity information, and a surface that describes the underlying object is needed for both performing computations on the object and to achieve its correct visualization. In this article we aim to survey the State-of-the-Art of the problem of reconstructing the surface of an object represented by a cloud of points. This set of points is assumed to be the result of a computer vision based 3D reconstruction pipeline.

关键词： Three dimensional displays Surface reconstruction Surface treatment Image reconstruction computer vision Pipelines Cameras

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Supervised local subspace learning for continuous head pose estimation

Supervised local subspace learning for continuous head pose ...

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作者： Huang, Dong Storer, Markus De La Torre, Fernando Bischof, Horst Robotics Institute Carnegie Mellon University United States Institute for Computer Graphics and Vision Graz University of Technology Austria University of Electronic Science and Technology of China China

ISBN: (纸本)9781457703942

Head pose estimation from images has recently attracted much attention in computer vision due to its diverse applications in face recognition, driver monitoring and human computer interaction. Most successful approaches to head pose estimation formulate the problem as a nonlinear regression between image features and continuous 3D angles (i.e. yaw, pitch and roll). However, regression-like methods suffer from three main drawbacks: (1) They typically lack generalization and overfit when trained using a few samples. (2) They fail to get reliable estimates over some regions of the output space (angles) when the training set is not uniformly sampled. For instance, if the training data contains under-sampled areas for some angles. (3) They are not robust to image noise or occlusion. To address these problems, this paper presents Supervised Local Subspace Learning (SL2), a method that learns a local linear model from a sparse and non-uniformly sampled training set. SL2 learns a mixture of local tangent spaces that is robust to under-sampled regions, and due to its regularization properties it is also robust to over-fitting. Moreover, because SL2 is a generative model, it can deal with image noise. Experimental results on the CMU Multi-PIE and BU-3DFE database show the effectiveness of our approach in terms of accuracy and computational complexity. © 2011 IEEE.

关键词： Face recognition

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Detection of interest points in turbid underwater images

Detection of interest points in turbid underwater images

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OCEANS - Europe

作者： Rafael Garcia Nuno Gracias Computer Vision and Robotics Group University of Girona Girona Spain

Our research is motivated by an evident lack of evaluation of recent image matching techniques for applications in underwater vision. This paper is a first step in this direction. This work compares the performance of popular salient keypoint detectors on images degraded by turbidity. We show that, as opposed to over-land, on images acquired in water medium, Hessian-based approaches outperform their Laplacian and Harris counterparts. Fast Hessian, the detector of the Speeded Up Robust Features (SURF) matching technique, is recognized to be the best method for scale-invariant detection. Conversely, when invariance to scale is not required, a combination of standard Hessian and Harris with sub-pixel accuracy and non-maxima suppression is more accurate. The objective of our work was also to create and distribute a reference set of turbid images, which can be used to evaluate processing, detection, description and matching techniques for underwater applications. We present a collection of 36 images acquired by a specially designed trinocular system under 12 gradually increasing turbidity levels. We also draw attention to image quality assessment method called SSIM, Structural SIMilarity index, which reliably quantifyes degradation of image quality caused by turbidity. As a whole, the major goal of this paper is to provide an updated reference for researchers dealing with keypoint detection in underwater imaging.

关键词： Detectors Cameras Scattering Visualization Laplace equations Accuracy Dairy products

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Attracting talent to increase interest for engineering among secondary school students

Attracting talent to increase interest for engineering among...

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IEEE Education Engineering (EDUCON)

作者： Miquel Villanueva Xevi Cufí Andrés ElFakdi Pere Ridao Rafael Garcia Computer Vision and Robotics Group University of Girona Girona Spain

This paper reports our experience in developing a team-based project activity to promote engineering programs among secondary school students. The aim of the activity is to increase the interest of students for science and technology in general, but also to promote engineering skills, capabilities and values, leading to attract more secondary school students to enrollment for engineering programs. Simple theoretical concepts are illustrated through hands-on experimentation. To achieve this goal, the students build a Remotely Operated Underwater Robot in a 2½-day workshop. The robot is built using low-cost materials and the students customize their own design over the different phases of the workshop. Once the activity is completed, every team understands that with teamwork, effort and a good working strategy, every problem can be overcome. At the end of the activity, a survey is conducted through an assessment survey questionnaire which reflects different aspects related with the development of the activity and the degree to which learning of its different facets has been achieved. The responses and feedback from students serve not only to evaluate the workshop, but also as feedback for future fine-tuning of the different phases as pedagogical learning tools.

关键词： Robots Conferences DC motors Educational institutions Vehicles Engineering education Wires

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Learning multi-lane trajectories using vehicle-based vision

Learning multi-lane trajectories using vehicle-based vision

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International Conference on computer vision Workshops (ICCV Workshops)

作者： Sayanan Sivaraman Brendan Morris Mohan Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego USA

Safe operation of a motor vehicle requires awareness of the current traffic situation as well as the ability to predict future maneuvers. In order to provide an intelligent vehicle the ability to make predictions, this work proposes a framework for understanding the driving situation based on vehicle mounted vision sensors. Vehicles are tracked using Kalman filtering based on a vision-based system that detects and tracks using a combination of monocular and stereo-vision. The vehicles' full trajectories are recorded, and a data-driven learning framework has been applied to automatically learn surround behaviors. By learning based on observations, the ADAS system is being trained by experience. Learned trajectories have been compared between dense and free-flowing traffic conditions. Preliminary experimental results using real-world multi-lane highways show the basic promise of this approach. Future research directions are discussed.

关键词： Vehicles Trajectory Hidden Markov models Mathematical model Detectors Equations Training

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Radiometric Calibration by Transform Invariant Low-rank Structure

Radiometric Calibration by Transform Invariant Low-rank Stru...

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IEEE Conference on computer vision and Pattern Recognition

作者： Joon-Young Lee Boxin Shi Yasuyuki Matsushita In-So Kweon Katsushi Ikeuchi Robotics and Computer Vision Lab KAIST The University of Tokyo Microsoft Research Asia

ISBN: (纸本)9781457703942

We present a robust radiometric calibration method that capitalizes on the transform invariant low-rank structure of sensor irradiances recorded from a static scene with different exposure times. We formulate the radiometric calibration problem as a rank minimization problem. Unlike previous approaches, our method naturally avoids over-fitting problem;therefore, it is robust against biased distribution of the input data, which is common in practice. When the exposure times are completely unknown, the proposed method can robustly estimate the response function up to an exponential ambiguity. The method is evaluated using both simulation and real-world datasets and shows a superior performance than previous approaches.

关键词： exposure time incoming data Radiation Response function Invariant Transform CALIBRATION METHODS

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Retinal vessel tortuosity evaluation via circular hough transform

Retinal vessel tortuosity evaluation via circular hough tran...

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2011 18th Iranian Conference of Biomedical Engineering, ICBME 2011

作者： Ghadiri, Farnoosh Pourreza, Hamidreza Banaee, Touka Delgir, Morteza Computer Engineering Department Machine Vision Lab Ferdowsi University Mashhad Iran Ophthalmic Research Center Khatam-Al-Anbia Hospital Medical Science University Mashhad Iran Computer Science Department Robotics Lab Northeastern University United States

ISBN: (纸本)9781467310055

Retinal vessel tortuosity has shown to be significantly associated with cardiovascular diseases such as hypertension and diabetes. Despite importance of this field a few techniques have been proposed yet. All previous methods rely on a vessel extraction phase, which its accuracy affects final output and also time consuming. Nobility of presented algorithm is to introduce a method for evaluating retinal vessel tortuosity without any explicit vessel detection. We use the Circular Hough Transform (CHT) based on gradient field of the retinal image. Each vessel curve is detected as a semi-circle by Hough transform and tortuosity of the curve is determined with the help of accumulated value of circle center and its radius. As there are no any specific database for tortuosity evaluation, the algorithm was tasted on database consisting of 40 images, mixture of DRIVE database and images from Khatam-Al-Anbia Hospital consisting of 40 retinal images, of which 20 were tortuous and 20 were non-tortuous. The proposed algorithm can achieve classification rate of 92% along with less computation time in compare of previous methods. © 2011 IEEE.

关键词： Database systems

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Supervised texture segmentation through a multi-level pixel-based classifier based on specifically designed filters

Supervised texture segmentation through a multi-level pixel-...

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IEEE International Conference on Image Processing

作者： Jaime Melendez Xavier Girones Domenec Puig Intelligent Robotics and Computer Vision Group Department of Computer Science and Mathematics Rovira i Virgili University Spain

This paper presents a new, efficient technique for supervised texture segmentation based on a set of specifically designed filters and a multi-level pixel-based classifier. Filter design is carried out by means of a neural network, which is trained to maximize the filters' discrimination power among the texture classes under consideration. Texture features obtained with these filters are then processed by a classification scheme that utilizes multiple evaluation window sizes following a top-down approach, which iteratively refines the resulting segmentation. The proposed technique is compared to previous supervised texture segmenters by using both synthetic compositions and real outdoor textured images.

关键词： Filter banks Image segmentation Feature extraction Gabor filters Adaptive filters Conferences Support vector machines

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Hierarchical congestion control for robotic swarms

Hierarchical congestion control for robotic swarms

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2011 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Vinicius Graciano Santos Luiz Chaimowicz Vision and Robotics Laboratory (VeRLab) Computer Science Department Federal University Minas Gerais Brazil

Safe and efficient navigation of robotic swarms is an important research problem. One of the main challenges in this area is to avoid congestion, which usually happens when large groups of robots share the same environment. In this paper, we propose the use of hierarchical abstractions in conjunction with simple traffic control rules based on virtual forces to avoid congestion in swarm navigation. We perform simulated and real experiments in order to study the feasibility and effectiveness of the proposed algorithm. Results show that our approach allows the swarm to navigate without congestions in a smooth and coherent fashion, being suitable for large groups of robots.

关键词： Robot kinematics Robot sensing systems Collision avoidance Navigation Force Aerospace electronics

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