Wide Area Scene Analysis in Vision Network
Networks of cameras are nowadays installed in various places. However, most of the data collected by such networks are analyzed manually, thus severely limiting their application. In this research, which is divided into different sub-projects, we are studying the core scientific and technical issues related to camera networks, such as information fusion, network control, activity analysis, the interplay between networking and computer vision, and computational complexity.
Camera Network Tracking and Re-identification
In many computer vision tasks it is often desirable to identify and monitor people as they move through a network of non-overlapping cameras. This is especially challenging as for a network of cameras issues such as changes of scale, illumination, viewing angle and pose start to arise. In this project we try to address this inter camera person association problem. We have shown that incorporating a consistency requirement of re-identification results across the camera network can significantly improve the re-identification performance even in the challenging scenarios where the illumination changes between the cameras are large.
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Sample Publications
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Exploiting Temporal Coherence for Self-Supervised One-shot Video Re-identification
D. Raychaudhuri, A. Roy-Chowdhury, European Conference on Computer Vision (ECCV), 2020.
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Exploiting Transitivity for Learning Person Re-identification Models on a Budget
S. Roy, S. Paul, N. Young and A. Roy-Chowdhury, IEEE Conf. on Computer Vision and Pattern Recognition, 2018.
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Unsupervised Adaptive Re-identification in Open World Dynamic Camera Networks
R. Panda, A. H. Bhuiyan, V. Murino and A. Roy-Chowdhury, IEEE Conf. on Computer Vision and Pattern Recognition, 2017 (Spotlight).
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Continuous adaptation of multi-camera person identification models through sparse non-redundant representative selection [Supplemental Material]
A. Das, R. Panda, A. Roy-Chowdhury, Computer Vision and Image Understanding, 2016.
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Temporal Model Adaptation for Person Re-Identification
N. Martinel, C. Micheloni, A. Roy-Chowdhury, European Conf. on Computer Vision, 2016.
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Tracking multiple interacting targets in a camera network
S. Zhang, Y. Zhu, and A. K. Roy-Chowdhury, Computer Vision and Image Understanding special issue on Image Understanding for Real-world Distributed Video Networks. 2015.
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Re-Identification in the Function Space of Feature Warps [Supplemental Material]
A. Das, N. Martinel, C. Micheloni, A. Roy-Chowdhury, IEEE Trans. on Pattern Analysis and Machine Intelligence, 2015.
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A Camera Network Tracking (CamNet) Dataset and Performance Baseline [CamNet Dataset]
S. Zhang, E. Staudt, T. Faltemier, A. Roy-Chowdhury, IEEE Winter Conference on Applications of Computer Vision, 2015.
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Consistent Re-identification In A Camera Network [Supplemental Material] [Code]
A. Das, A. Chakraborty, A. Roy-Chowdhury, European Conf. on Computer Vision, 2014.
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A Stochastic Graph Evolution Framework for Robust Multi-Target Tracking,
B. Song, T. Jeng, E. Staudt, A. Roy-Chowdhury, European Conference on Computer Vision, 2010.
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Distributed Multi-Target Tracking In A Self-Configuring Camera Network
C. Soto, B. Song, A. Roy-Chowdhury, IEEE Conf. on Computer Vision and Pattern Recognition, 2009.
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Robust Tracking in A Camera Network: A Multi-Objective Optimization Framework
B. Song and A. Roy-Chowdhury, IEEE Journal on Selected Topics in Signal Processing: Special Issue on Distributed Processing in Vision Networks, August 2008.
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Stochastic Adaptive Tracking In A Camera Network
B. Song, A. Roy-Chowdhury, IEEE Intl. Conf. on Computer Vision, 2007.
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Distributed Estimation
In this project, we are developing methods for estimation and control in distributed camera networks. Specifically, we have looked at the following problems.
- Distributed estimation algorithms that are aware of the specific constraints of camera networks
- Distributed control for collaborative and opportunistic sensing in wide-area camera networks
Demos
Information-Weighted Consensus in a Distributed Camera Network
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Sample Publications
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Exploiting Transitivity for Learning Person Re-identification Models on a Budget
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Unsupervised Adaptive Re-identification in Open World Dynamic Camera Networks
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A. Das, R. Panda, A. Roy-Chowdhury, Computer Vision and Image Understanding, 2016.
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Temporal Model Adaptation for Person Re-Identification
N. Martinel, C. Micheloni, A. Roy-Chowdhury, European Conf. on Computer Vision, 2016.
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A Camera Network Tracking (CamNet) Dataset and Performance Baseline
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Consistent Re-identification In A Camera Network
A. Das, A. Chakraborty, A. Roy-Chowdhury, European Conf. on Computer Vision, 2014.
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A Stochastic Graph Evolution Framework for Robust Multi-Target Tracking,
B. Song, T. Jeng, E. Staudt, A. Roy-Chowdhury, European Conference on Computer Vision, 2010.
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Distributed Multi-Target Tracking In A Self-Configuring Camera Network
C. Soto, B. Song, A. Roy-Chowdhury, IEEE Conf. on Computer Vision and Pattern Recognition, 2009.
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Robust Tracking in A Camera Network: A Multi-Objective Optimization Framework
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Stochastic Adaptive Tracking In A Camera Network
B. Song, A. Roy-Chowdhury, IEEE Intl. Conf. on Computer Vision, 2007.
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Active Sensing
We are developing methods for optimizing the image acquisition capabilities of the cameras so as to maximize the performance of the methods used to analyze these image. This needs to be done through collaboration between the cameras in a network, as each camera's parameters entail constraints on the others. We have developed distributed control methods for collaborative and opportunistic sensing in wide-area camera networks.
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Sample Publications
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Opportunistic Image Acquisition of Individual and Group Activities in a Distributed Camera Network
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Distributed Constrained Optimization for Bayesian Opportunistic Visual Sensing
A. Morye, C. Ding, J. A. Farrell, A. Roy-Chowdhury, IEEE Trans. on Control Systems Technology, 2014.
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Collaborative Sensing In A Distributed PTZ Camera Network
C. Ding, B. Song, A. Morye, J. A. Farrell, A. Roy-Chowdhury, IEEE Trans. on Image Processing, 2012.
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Coordinated Sensing and Tracking for Mobile Camera Platforms
C. Ding, A. Morye, J. A. Farrell, A. Roy-Chowdhury, American Controls Conf., 2012.
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Parts of this work have been supported by the NSF CPS program under the project Distributed Sensing, Learning and Control in Dynamic Environments.