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Activity recognition in wide aerial video surveillance using entity relationship models 12

Activity recognition in wide aerial video surveillance using...

引用

20th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2012

作者： Choi, Jongmoo Dumortier, Yann Prokaj, Jan Medioni, Gérard Computer Vision Lab. Institute for Robotics and Intelligent Systems University of Southern California United States

ISBN: (纸本)9781450316910

We present the design and implementation of an activity recognition system in wide area aerial video surveillance using Entity Relationship Models (ERM). In this approach, finding an activity is equivalent to sending a query to a Relational DataBase Management System (RDBMS). By incorporating reference imagery and Geographic Information System (GIS) data, tracked objects can be associated with physical meanings, and several high levels of reasoning, such as traffic patterns or abnormal activity detection, can be performed. We demonstrate that different types of activities, with hierarchical structure, multiple actors, and context information, are effectively and efficiently defined and inferred using the ERM framework. We also show how visual tracks can be better interpreted as activities by using geo information. Experimental results on both real visual tracks and GPS traces validate our approach. © 2012 Authors.

关键词： Security systems

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OUR-CVFH - Oriented, unique and repeatable clustered viewpoint feature histogram for object recognition and 6DOF pose estimation

OUR-CVFH - Oriented, unique and repeatable clustered viewpoi...

引用

Joint 34th Symposium of the German Association for Pattern Recognition, DAGM 2012 and 36th Symposium of the Austrian Association for Pattern Recognition, OAGM 2012

作者： Aldoma, Aitor Tombari, Federico Rusu, Radu Bogdan Vincze, Markus Vision4Robotics Group ACIN Vienna University of Technology Austria Computer Vision Lab. DEIS - ARCES University of Bologna Italy Open Perception Inc. United States

ISBN: (纸本)9783642327162

We propose a novel method to estimate a unique and repeatable reference frame in the context of 3D object recognition from a single viewpoint based on global descriptors. We show that the ability of defining a robust reference frame on both model and scene views allows creating descriptive global representations of the object view, with the beneficial effect of enhancing the spatial descriptiveness of the feature and its ability to recognize objects by means of a simple nearest neighbor classifier computed on the descriptor space. Moreover, the definition of repeatable directions can be deployed to efficiently retrieve the 6DOF pose of the objects in a scene. We experimentally demonstrate the effectiveness of the proposed method on a dataset including 23 scenes acquired with the Microsoft Kinect sensor and 25 full-3D models by comparing the proposed approach with state-of-the-art global descriptors. A substantial improvement is presented regarding accuracy in recognition and 6DOF pose estimation, as well as in terms of computational performance. © 2012 Springer-Verlag.

关键词： Object recognition

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Supervised learning of hidden and non-hidden 0-order affordances and detection in real scenes

Supervised learning of hidden and non-hidden 0-order afforda...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Aitor Aldoma Federico Tombari Markus Vincze Vision4Robotics Group Automation and Control Institute University of Technology Vienna Austria Computer Vision Lab DEIS-ARCES University of Bologna Italy

The ability to perceive possible interactions with the environment is a key capability of task-guided robotic agents. An important subset of possible interactions depends solely on the objects of interest and their position and orientation in the scene. We call these object-based interactions 0-order affordances and divide them among non-hidden and hidden whether the current configuration of an object in the scene renders its affordance directly usable or not. Conversely to other works, we propose that detecting affordances that are not directly perceivable increase the usefulness of robotic agents with manipulation capabilities, so that by appropriate manipulation they can modify the object configuration until the seeked affordance becomes available. In this paper we show how 0-order affordances depending on the geometry of the objects and their pose can be learned using a supervised learning strategy on 3D mesh representations of the objects allowing the use of the whole object geometry. Moreover, we show how the learned affordances can be detected in real scenes obtained with a low-cost depth sensor like the Microsoft Kinect through object recognition and 6D0F pose estimation and present results for both learning on meshes and detection on real scenes to demonstrate the practical application of the presented approach.

关键词： Solid modeling Robots Training Design automation Histograms Object recognition Computational modeling

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Object recognition using saliency maps and HTM learning

Object recognition using saliency maps and HTM learning

引用

2012 IEEE International Conference on Imaging Systems and Techniques, IST 2012

作者： Kostavelis, Ioannis Nalpantidis, Lazaros Gasteratos, Antonios Laboratory of Robotics and Automation Department of Production and Management Engineering Democritus University of Thrace Vas. Sofias 12 GR-67100 Xanthi Greece Computer Vision and Active Perception Lab. Centre for Autonomous Systems Royal Institute of Technology - KTH SE-100 44 Stockholm Sweden

ISBN: (纸本)9781457717741

In this paper a pattern classification and object recognition approach based on bio-inspired techniques is presented. It exploits the Hierarchical Temporal Memory (HTM) topology, which imitates human neocortex for recognition and categorization tasks. The HTM comprises a hierarchical tree structure that exploits enhanced spatiotemporal modules to memorize objects appearing in various orientations. In accordance with HTM's biological inspiration, human vision mechanisms can be used to preprocess the input images. Therefore, the input images undergo a saliency computation step, revealing the plausible information of the scene, where a human might fixate. The adoption of the saliency detection module releases the HTM network from memorizing redundant information and augments the classification accuracy. The efficiency of the proposed framework has been experimentally evaluated in the ETH-80 dataset, and the classification accuracy has been found to be greater than other HTM systems. © 2012 IEEE.

关键词： Object recognition

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Radiometric calibration by transform invariant low-rank structure

Radiometric calibration by transform invariant low-rank stru...

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

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. © 2011 IEEE.

关键词： Radiometry

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Retinal vessel tortuosity evaluation via circular hough transform

Retinal vessel tortuosity evaluation via circular hough tran...

引用

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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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

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

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Support Aggregation via Non-linear Diffusion with Disparity-Dependent Support-Weights for Stereo Matching

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9th Asian Conference on computer vision

作者： Yoon, Kuk-Jin Jeong, Yekeun Kweon, In So Computer Vision Lab. Dept. Information and Communications GIST South Korea Robotics and Computer Vision Lab. KAIST South Korea

ISBN: (纸本)9783642123061

In stereo matching, homogeneous areas, depth continuity areas, and occluded areas need more attention. Many methods try to handle pixels in homogeneous areas by propagating supports. As a result, pixels in homogeneous areas get assigned disparities inferred from the disparities of neighboring pixels. However, at the same time, pixels in depth discontinuity areas get supports from different depths and/or from occluded pixels, and resultant disparity maps are easy to be blurred. To resolve this problem, we propose a non-linear diffusion-based support aggregation method. Supports are iteratively aggregated with the support-weights, while adjusting the support-weights according to disparities to prevent incorrect supports from different depths and/or occluded pixels. As a result, the proposed method yields good results not only in homogeneous areas but also in depth discontinuity areas as the iteration goes on without the critical degradation of performance.

关键词： Pixels

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Attention estimation by simultaneous observation of viewer and view

Attention estimation by simultaneous observation of viewer a...

引用

2010 IEEE computer Society Conference on computer vision and Pattern Recognition - Workshops, CVPRW 2010

作者： Doshi, Anup Trivedi, Mohan M. Computer Vision and Robotics Research Lab University of California San Diego CA 92093-0434 United States

ISBN: (纸本)9781424470297

We introduce a new approach to analyzing the attentive state of a human subject, given cameras focused on the subject and their environment. In particular, the task of analyzing the focus of attention of a human driver is of primary concern. Up to 80% of automobile crashes are related to driver inattention;thus it is important for an Intelligent Driver Assistance System (IDAS) to be aware of the driver state. We present a new Bayesian paradigm for estimating human attention specifically addressing the problems arising in dynamic situations. The model incorporates vision-based gaze estimation, "top-down"-and "bottomup"-based visual saliency maps, and cognitive considerations such as inhibition of return and center bias that affect the relationship between gaze and attention. Results demonstrate the validity on real driving data, showing quantitative improvements over systems using only gaze or only saliency, and elucidate the value of such a model for any human-machine interface. © 2010 IEEE.

关键词： Accidents

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Pushing the envelope of modern methods for bundle adjustment

Pushing the envelope of modern methods for bundle adjustment

引用

Conference on computer vision and Pattern Recognition (CVPR)

作者： Yekeun Jeong David Nister Drew Steedly Richard Szeliski In-So Kweon Robotics and Computer Vision Lab. KAIST Microsoft Research South Korea Robotics and Computer Vision Lab. KAIST Microsoft Research Robotics and Computer Vision Lab. KAIST Microsoft Research USA

In this paper, we present results and experiments with several methods for bundle adjustment, producing the fastest bundle adjuster ever published. The fastest methods work with the well known reduced camera system and handle the block-sparse pattern arising in the reduced camera system in a natural way. Adapting to the naturally arising block-sparsity allows the use of BLAS3, efficient memory handling, fast variable ordering, and customized sparse solving all at the same time. We present two methods, one using exact minimum degree ordering and block-based LDL solving, and one using block-based preconditioned conjugate gradient, both on the reduced camera system. We show experimentally that the adaptation to the natural block sparsity allows both these methods to perform better than previous ones. Further speed improvements are achieved by the novel use of embedded point iterations. The embedded point iterations take place inside each camera update step, yielding a higher cost decrease from each camera update step. This is especially true for points projecting far out on the flatter region of the robustifier.

关键词： Cameras Robot vision systems Large-scale systems computer vision Costs Convergence Character generation Robustness Frequency conversion Humans

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