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Analysis and query of person-vehicle interactions in homography domain

Analysis and query of person-vehicle interactions in homogra...

4th ACM International Workshop on Video Surveillance and Sensor Networks, VSSN'06, co-located with the 2006 ACM International Multimedia Conference

作者： Park, Sangho Trivedi, Mohan M. Computer Vision and Robotics Research Lab. University of California San Diego CA United States

ISBN: (纸本)1595934960

This paper presents an efficient and robust paradigm for analysis and query of moving-object interactions in planar homography *** and vehicle activities/interactions are analyzed for situational awareness by using a multi-perspective *** homography constraints are exploited to extract view-invariant object features including footage area and velocity of objects on the ground plane. Spatio-temporal relationships between person-and vehicle-tracks are represented by a semantic event grammar. Semantic-level information of the situation is achieved with the anticipation of possible directions of near-future tracks using piecewise velocity history. An efficient query paradigm is proposed by histogram-based approximation of probability density functions of objects and by quad-tree indexing. Experimental data show promising *** framework can be applied to applications for enhanced situational awareness such as disaster prevention,human interactions in structured environments,and crowd movement analysis in wide-view areas. Copyright 2006 ACM.

关键词： Data reduction

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Generalization accuracy of a fast 2-D shape retrieval method

Generalization accuracy of a fast 2-D shape retrieval method

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Proceedings of the International Conference on Imaging Science, Systems and Technology, CISST'03

作者： Super, Boaz J. Computer Vision and Robotics Lab. Computer Science Department University of Illinois at Chicago Chicago IL United States

In recent work, we presented a correspondence-based approach for real-time retrieval from databases of 2-D shapes. The system performs with high speed and accuracy relative to other published systems as measured on a widely used benchmark dataset. In this paper, we test the generalization accuracy of the approach;i.e., its ability to correctly retrieve shapes from a shape database when the query shapes are not contained in the database. The experimental results show that the system's accuracy on novel inputs is nearly as high as its accuracy on shapes that are already contained in the database, demonstrating that the approach has good generalization accuracy. This result provides additional support for the use of the proposed approach for shape retrieval and object recognition applications.

关键词： Image retrieval

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

Activity recognition in wide aerial video surveillance using...

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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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The "Castelet": A dynamically reconfigurable stage for performing arts 07

The "Castelet": A dynamically reconfigurable stage for perfo...

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ACM SIGGRAPH 2007 Sketches, SIGGRAPH'07

作者： Jobin, Jean-Philippe Comtois, Sylvain Gosselin, Clément Faguy, Robert Laurendeau, Denis Robotics Laboratory Computer Vision and Systems Lab. LANTISS Laval University Quebec City Canada

The hero jumped down the wall, escalated the hill, slid down the rock, climbed the stairs and finally left the vilain behind...In this classical scene, the hero has to move on different types of terrain. Recreating su...

ISBN: (纸本)9781450347266

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Optical flow estimation from a single motion-blurred image

arXiv

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arXiv 2021年

作者： Argaw, Dawit Mureja Kim, Junsik Rameau, Francois Cho, Jae Won Kweon, In So KAIST Robotics and Computer Vision Lab. Daejeon Korea Republic of

In most of computer vision applications, motion blur is regarded as an undesirable artifact. However, it has been shown that motion blur in an image may have practical interests in fundamental computer vision problems. In this work, we propose a novel framework to estimate optical flow from a single motion-blurred image in an end-to-end manner. We design our network with transformer networks to learn globally and locally varying motions from encoded features of a motion-blurred input, and decode left and right frame features without explicit frame supervision. A flow estimator network is then used to estimate optical flow from the decoded features in a coarse-to-fine manner. We qualitatively and quantitatively evaluate our model through a large set of experiments on synthetic and real motion-blur datasets. We also provide in-depth analysis of our model in connection with related approaches to highlight the effectiveness and favorability of our approach. Furthermore, we showcase the applicability of the flow estimated by our method on deblurring and moving object segmentation tasks. © 2021, CC BY.

关键词： Optical flows

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Restoration of video frames from a single blurred image with motion understanding

arXiv

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arXiv 2021年

作者： Argaw, Dawit Mureja Kim, Junsik Rameau, Francois Zhang, Chaoning Kweon, In So Kaist Robotics and Computer Vision Lab. Daejeon Korea Republic of

We propose a novel framework to generate clean video frames from a single motion-blurred image. While a broad range of literature focuses on recovering a single image from a blurred image, in this work, we tackle a more challenging task i.e. video restoration from a blurred image. We formulate video restoration from a single blurred image as an inverse problem by setting clean image sequence and their respective motion as latent factors, and the blurred image as an observation. Our framework is based on an encoder-decoder structure with spatial transformer network modules to restore a video sequence and its underlying motion in an end-to-end manner. We design a loss function and regularizers with complementary properties to stabilize the training and analyze variant models of the proposed network. The effectiveness and transferability of our network are highlighted through a large set of experiments on two different types of datasets: camera rotation blurs generated from panorama scenes and dynamic motion blurs in high speed videos. © 2021, CC BY.

关键词： Restoration

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Learning a Deep Convolutional Network for Light-Field Image Super-Resolution

Learning a Deep Convolutional Network for Light-Field Image ...

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International Conference on computer vision Workshops (ICCV Workshops)

作者： Youngjin Yoon Hae-Gon Jeon Donggeun Yoo Joon-Young Lee In So Kweon Robotics and Computer Vision Lab KAIST

Commercial Light-Field cameras provide spatial and angular information, but its limited resolution becomes an important problem in practical use. In this paper, we present a novel method for Light-Field image super-resolution (SR) via a deep convolutional neural network. Rather than the conventional optimization framework, we adopt a datadriven learning method to simultaneously up-sample the angular resolution as well as the spatial resolution of a Light-Field image. We first augment the spatial resolution of each sub-aperture image to enhance details by a spatial SR network. Then, novel views between the sub-aperture images are generated by an angular super-resolution network. These networks are trained independently but finally finetuned via end-to-end training. The proposed method shows the state-of-the-art performance on HCI synthetic dataset, and is further evaluated by challenging real-world applications including refocusing and depth map estimation.

关键词： Spatial resolution Cameras Lenses Image restoration Neural networks

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REFLECTION REMOVAL USING DISPARITY AND GRADIENT-SPARSITY VIA SMOOTHING ALGORITHM

REFLECTION REMOVAL USING DISPARITY AND GRADIENT-SPARSITY VIA...

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IEEE International Conference on Image Processing

作者： Tharatch Sirinukulwattana Gyeongmin Choe In So Kweon Robotics and Computer Vision Lab KAIST

ISBN: (纸本)9781479983407

The purpose of this paper is to introduce a new method for removing reflections from multi-view images taken through a transparent medium, such as pane glass. Our method utilizes an optimization approach based on the probabilistic model of relative smoothness algorithm, which exploits gradient value to separate the image into two sub-layers. As this algorithm has certain limitations on removing reflections, we improve upon it by imposing a gradient-sparsity constraint. This allows the type of reflection captured within a camera's focal length to be effectively removed. We also introduce another constraint on a disparity map which smooths specific areas of reflection layer while simultaneously preserves the sharpness of the main object. These two major contributions are proven to be sufficient in producing high-quality images. Our algorithm demonstrates good results compared with other existing methods as most of the reflection spots have been removed, and the computational time of our system is arguably fast.

关键词： Reflection removal Layer separation Reflection reflecting layer smoothing algorithms images Probabilistic Model Sharpness computational time

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A two-stage multi-view analysis framework for human activity and interactions

A two-stage multi-view analysis framework for human activity...

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2007 IEEE Workshop on Motion and Video Computing, WMVC 2007

作者： Park, Sangho Trivedi, Mohan M. Computer Vision and Robotics Research Lab. University of California San Diego San Diego CA 92037

ISBN: (纸本)0769527930

This paper presents a new framework for a multi-stage multi-view approach for human interactions and activity analysis. The analysis is performed in a distributed vision system that synergistically integrate track- and body-level representations across multiple cameras. Our system aims at versatile and easily-deployable system that does not require careful camera calibration. Main contributions of the paper are: (1) context-dependent camera handover for occlusion handling, (2) switching the multi-stage analysis between track- and body-level representations, and (3) a hypothesis-verification paradigm for top-down feedback exploiting spatio-temporal constraints inherent in human interaction. Experimental evaluation shows the efficacy of the proposed system for analyzing multi-person interactions. Current implementation uses two views, but extension to more views is straightforward. © 2007 IEEE.

关键词： Human computer interaction

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Homography-based analysis of people and vehicle activities in crowded scenes

Homography-based analysis of people and vehicle activities i...

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7th IEEE Workshop on Applications of computer vision, WACV 2007

作者： Park, Sangho Trivedi, Mohan M. Computer Vision and Robotics Research Lab. University of California San Diego San Diego CA 92037

ISBN: (纸本)0769527949

This paper presents an new framework for homographybased analysis of pedestrian-vehicle activity in crowded scenes. Planar homography constraint is exploited to extract view-invariant object features including footage area and velocity of objects on the ground plane. Spatiotemporal relationships between people- and vehicle- tracks are represented by a semantic event. Context awareness of the situation is achieved by the estimated density distribution of objects and the anticipation of possible directions of near-future tracks using piecewise velocity history. Singleview and multi-view based homography mapping options are compared. Our framework can be used to enhance situational awareness for disaster prevention, human interactions in structured environments, and crowd movement analysis at wide regions. © 2007 IEEE.

关键词： Feature extraction

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