The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Bayesian Poisson regression for crowd counting
Abstract
Poisson regression models the noisy output of a counting function as a Poisson random variable, with a log-mean parameter that is a linear function of the input vector. In this work, we analyze Poisson regression in a Bayesian setting, by introducing a prior distribution on the weights of the linear function. Since exact inference is analytically unobtainable, we derive a closed-form approximation to the predictive distribution of the model. We show that the predictive distribution can be kernelized, enabling the representation of non-linear log-mean functions. We also derive an approximate marginal likelihood that can be optimized to learn the hyperparameters of the kernel. We then relate the proposed approximate Bayesian Poisson regression to Gaussian processes. Finally, we present experimental results using Bayesian Poisson regression for crowd counting from low-level features.
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Cites
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Privacy preserving crowd monitoring: Counting people without people models or tracking
Chan, A. B., Liang, Z.-S. J., & Vasconcelos, N. (2008) · 2008 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2008.4587569 · Cited by 1,172
Self-citationThe Statistical Analysis of Variance-Heterogeneity and the Logarithmic Transformation
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Modeling, Clustering, and Segmenting Video with Mixtures of Dynamic Textures
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Self-citationA log gamma model and its maximum likelihood estimation
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Cited by
Scale Aggregation Network for Accurate and Efficient Crowd Counting
Cao, X., Wang, Z., Zhao, Y., & Su, F. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01228-1_45 · Cited by 733
Crowd Analysis Using Computer Vision Techniques
Silveira Jacques Junior, J., Musse, S., & Jung, C. (2010) · IEEE Signal Processing Magazine · doi:10.1109/msp.2010.937394 · Cited by 343
Multi-scale Deep Learning Architectures for Person Re-identification
Qian, X., Fu, Y., Jiang, Y.-G., Xiang, T., & Xue, X. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.577 · Cited by 319
Leveraging Unlabeled Data for Crowd Counting by Learning to Rank
Liu, X., van de Weijer, J., & Bagdanov, A. D. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00799 · Cited by 308
DeepSetNet: Predicting Sets with Deep Neural Networks
Rezatofighi, S. H., B. G., V. K., Milan, A., Abbasnejad, E., Dick, A., & Reid, I. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.561 · Cited by 45
Metadata
- Authors
- Chan, A. B., & Vasconcelos, N.
- Venue
- 2009 IEEE 12th International Conference on Computer Vision
- Publisher
- IEEE
- Published
- 2009-09
- Pages
- 545-551
- OpenAlex
- W2541389513
- Cited by
- 432
- References
- 15
- FWCI
- 3.53
- Type
- conference paper
- Language
- en
- Open access
- closed
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