The Recognition of Human Movement Using Temporal Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Statistical Method for People Counting in Crowded Environments
ICIAP '07 Proceedings of the 14th International Conference on Image Analysis and Processing
Multi-modal tracking of people using laser scanners and video camera
Image and Vision Computing
Pedestrian Counting Using an IR Line Laser
ICHIT '08 Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology
Evaluation of a "smart" pedestrian counting system based on echo state networks
EURASIP Journal on Embedded Systems - Challenges on complexity and connectivity in embedded systems
Recognition of human actions using texture descriptors
Machine Vision and Applications - Special Issue on Dynamic Textures in Video
| Hi-index | 0.00 |
An accurate estimation of the number of people entering/ leaving a controlled area is an interesting capability for automatic surveillance systems. Potential applications where this technology can be applied include those related to security, safety, energy saving or fraud control. In this paper we present a novel configuration of a multi-sensor system combining both visual and range data specially suited for troublesome scenarios such as public transportation. The approach applies probabilistic estimation filters on raw sensor data to create intermediate level hypothesis that are later fused using a certainty-based integration stage. Promising results have been obtained in several tests performed on a realistic test bed scenario under variable lightning conditions.