Automatic congestion detection system for underground platforms

By Benny P. L. Lo, Sergio A. Velastin. Proceedings of 2001 International Symposium on Intelligent Multimedia, Video and Speech Processing. ISIMP 2001 (IEEE Cat. No.01EX489), 2001

340 citations recorded by the source corpus.

Subfields: Building and Construction, Civil and Structural Engineering, Safety, Risk, Reliability and Quality

View Paper: https://www.semanticscholar.org/paper/070ec39457a5dec9c8e7f15cd8dc4e958dc32d23

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Building and Construction

1. Sumaya H. Ahmed
2. Khaled M. El-Sayed
3. Massimo Piccardi
4. Licia Capra
5. Shireen Elhabian

In Civil and Structural Engineering

1. Sumaya H. Ahmed
2. Khaled M. El-Sayed
3. Massimo Piccardi
4. Shireen Elhabian

In Safety, Risk, Reliability and Quality

1. Sumaya H. Ahmed
2. Khaled M. El-Sayed
3. Massimo Piccardi
4. Shireen Elhabian

Citations in the corpus

• Moving Object Detection in Spatial Domain using Background Removal Techniques - State-of-Art (2008, positive): “Median filtering defines the background to be the median at each pixel location of all the frames in the buffer [36, 42, 69-71].”
• Advances in View-Invariant Human Motion Analysis: A Review (2010, background): “Moreover Lo and Velastin [31] proposed to use the median value of the last n frames as the background model.”
• Detecting Moving Objects, Ghosts, and Shadows in Video Streams (2003, background): “In frame #103, the Bs curve still shows a nonnegligible value of FP; this is due to the still partially erroneous background shown in Fig.”
• Background subtraction techniques: a review (2004, neutral): “Lo and Velastin in [3] proposed to use the median value of the last n frames as the background model.”
• Avoiding the crowds: understanding Tube station congestion patterns from trip data (2012, background): “So far, CCTV cameras have only been used to detect (and not predict) ‘platform’ congestions [13]; this is useful for staff members to decide, for example, when to temporarily close stations in entry/exit to alleviate overcrowding.”
• A Self-Organizing Approach to Background Subtraction for Visual Surveillance Applications (2008, background): “The main tasks in visual surveillance systems include motion detection, object classification, tracking, activity understanding, Manuscript received November 13, 2007; revised March 26, 2008.”