Person and Vehicle Tracking in Surveillance Video

@inproceedings{Miller2007PersonAV,
  title={Person and Vehicle Tracking in Surveillance Video},
  author={Andrew Miller and Arslan Basharat and Brandyn Allen White and Jingen Liu and Mubarak Shah},
  booktitle={CLEAR},
  year={2007}
}
This evaluation for person and vehicle tracking in surveillance presented some new challenges. The dataset was large and very high-quality, but with difficult scene properties involving illumination changes, unusual lighting conditions, and complicated occlusion of objects. Since this is a well-researched scenario [1], our submission was based primarily on our existing projects for automated object detection and tracking in surveillance. We also added several new features that are practical… 
Robust multiple target tracking under occlusion using fragmented mean shift and Kalman filter
  • G. Phadke
  • Engineering
    2011 International Conference on Communications and Signal Processing
  • 2011
TLDR
This paper investigates how to improve the robustness of visual tracking method for multiple target tracking with occlusion handling and proposes weighted fragment based mean shift with Kalman filter with the consideration of color features of the target.
Mean LBP and modified fuzzy C-means weighted hybrid feature for illumination invariant mean-shift tracking
TLDR
Experimental results show that the proposed scheme can lead to better localization and robust tracking in challenging illumination scenarios, when compared to several existing tracking algorithms.
Suivi automatique de nageurs à partir des séquences vidéo : application à l'analyse des performances
Dans le but d’ameliorer les performances des nageurs professionnels, nous avons developpe, en collaboration avec la Federation Francaise de Natation, un systeme automatique de suivi a base des
Real Time Surveillance and Object Tracking
TLDR
Object tracking is a challenging task in surveillance and activity analysis and video transport has technical challenge when the wireless transmissions require high data rate and low latency.
People/vehicle classification by recurrent motion of skeleton features
TLDR
An object classification algorithm is proposed to classify the objects into persons and vehicles despite the presence of shadow and partial occlusion in mid-field video using recurrent motion image (RMI) of skeleton features.

References

SHOWING 1-6 OF 6 REFERENCES
Object tracking: A survey
TLDR
The goal of this article is to review the state-of-the-art tracking methods, classify them into different categories, and identify new trends to discuss the important issues related to tracking including the use of appropriate image features, selection of motion models, and detection of objects.
A noniterative greedy algorithm for multiframe point correspondence
  • K. ShafiqueM. Shah
  • Computer Science
    IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2005
TLDR
This work presents a framework for finding point correspondences in monocular image sequences over multiple frames by using a polynomial time algorithm for a restriction of the general problem of multiframe point correspondence, which is NP-hard for three or more frames.
A hierarchical approach to robust background subtraction using color and gradient information
  • O. JavedK. ShafiqueM. Shah
  • Environmental Science, Computer Science
    Workshop on Motion and Video Computing, 2002. Proceedings.
  • 2002
TLDR
This method provides the solution to some of the common problems that are not addressed by most background subtraction algorithms, such as fast illumination changes, repositioning of static background objects, and initialization of background model with moving objects present in the scene.
Automatically Tuning Background Subtraction Parameters using Particle Swarm Optimization
  • B. WhiteM. Shah
  • Computer Science
    2007 IEEE International Conference on Multimedia and Expo
  • 2007
TLDR
The proposed solution is to automate this task by using a particle swarm optimization (PSO) algorithm to maximize a fitness function compared to provided ground-truth images and the fitness function used is the F-measure, which is the harmonic mean of recall and precision.
Tracking and Object Classification for Automated Surveillance
TLDR
The issues that need to be resolved before fully automated outdoor surveillance systems can be developed are discussed, and solutions to some of these problems are presented.
Bayesian modeling of dynamic scenes for object detection
  • Yaser SheikhM. Shah
  • Computer Science
    IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2005
TLDR
An object detection scheme that has three innovations over existing approaches that is based on a model of the background as a single probability density, and the posterior function is maximized efficiently by finding the minimum cut of a capacitated graph.