People detection in low-resolution video with non-stationary background

Authors:
Jianguo Zhang;Shaogang Gong
Affiliations:
School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast, Belfast BT7 1NN, UK;Department of Computer Science, Queen Mary University of London, London E1 4NS, UK
Venue:
Image and Vision Computing
Year:
2009

Citing 14
Cited 1

The visual analysis of human movement: a survey

Computer Vision and Image Understanding
Robust Real-Time Periodic Motion Detection, Analysis, and Applications

IEEE Transactions on Pattern Analysis and Machine Intelligence
A Trainable System for Object Detection

International Journal of Computer Vision - special issue on learning and vision at the center for biological and computational learning, Massachusetts Institute of Technology
Contour Tracking by Stochastic Propagation of Conditional Density

ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Robust Real-Time Face Detection

International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints

International Journal of Computer Vision
Learning to Detect Objects in Images via a Sparse, Part-Based Representation

IEEE Transactions on Pattern Analysis and Machine Intelligence
Detecting Pedestrians Using Patterns of Motion and Appearance

International Journal of Computer Vision
Histograms of Oriented Gradients for Human Detection

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Multiple Object Class Detection with a Generative Model

CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Local Features and Kernels for Classification of Texture and Object Categories: A Comprehensive Study

International Journal of Computer Vision
Robust visual tracking for multiple targets

ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
Human detection using oriented histograms of flow and appearance

ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
A phase-based approach to the estimation of the optical flow field using spatial filtering

IEEE Transactions on Neural Networks

A review of vision-based systems for soccer video analysis

Pattern Recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we present a framework for robust people detection in low resolution image sequences of highly cluttered dynamic scenes with non-stationary background. Our model utilizes appearance features together with short- and long-term motion information. In particular, we boost Integral Gradient Orientation histograms of appearance and short-term motion. Outputs from the detector are maintained by a tracker to correct any misdetections. A Bayesian model is then deployed to further fuse long-term motion information based on correlation. Experiments show that our model is more robust with better detection rate compared to the model of Viola et al. [Michael J. Jones Paul Viola, Daniel Snow, Detecting pedestrians using patterns of motion and appearance, International Journal of Computer Vision 63(2) (2005) 153-161].