Crowd Counting in Still Images for RoboSoldier: A Survey

Authors

  • Vidhi Khanduja Department of Computer Science, Delhi University, Delhi – 110 007, India
  • Tendai Padenga Department of Computer Science, Gujarat Technological University, Gujarat – 382 424, India https://orcid.org/0000-0003-2839-5908

DOI:

https://doi.org/10.14429/dsj.19142

Keywords:

RoboSoldier, Location Information Loss, Convolutional Neural Networks

Abstract

Part of the ultimate key capabilities for a RoboSoldier will lie in its ability to count the total number of people within a crowd with pin-drop precision. Crowd Counting (CC) relates to the estimation of the existing number of objects within a still image or video frame. Crowd counting has been successfully used in a wide range of applications from gathering business intelligence, such as consumer shopping patterns and ensuring normal operating conditions, to urban planning for crowd safety and stability through traffic monitoring. However, crowd counting has a fair range of its challenges like, high cluttering, varying illumination, severe occlusion, Perspective Distortion (PD), Irregular Object Distribution (IOD), non-object scales, and Location Information Loss (LIL)...

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Published

2025-03-24

How to Cite

Vidhi Khanduja, & Tendai Padenga. (2025). Crowd Counting in Still Images for RoboSoldier: A Survey . Defence Science Journal, 75(2), 167–178. https://doi.org/10.14429/dsj.19142

Issue

Section

Computers & Systems Studies