earticle

논문검색

Automated Surveillance in Distributed, Visual Networks : An Empirical Comparison of Recent Algorithms

초록

영어

A number of algorithms have been recently proposed for automatic intruder detection from CCTV images. Past researchers have typically tested these algorithms on centralized networks where all images are transmitted to a central control room. This paper demon- strates the applicability of a selection of such algorithms to a distributed network of wireless sensors. A distributed network of wireless visual sensors was simulated using a number of high-resolution webcams setup in the hallways of an academic building. The selected algo- rithms were then applied in a distributed fashion at each node. An empirical comparison of the most popular of the recent algorithms on a simulation of a wireless sensor network was thus obtained. This paper provides corroborating evidence in support of the most effective of such algorithms to the problem of automatic anomaly detection from image streams.

목차

Abstract
 1. Introduction
  1.1 Organization of Paper
 2. Algorithmic Bases
  2.1 Kernel Functions
  2.2 Kernel-based Online Anomaly Detection Algorithm
  2.3 Kernel Density Estimation
  2.4 Kernel Estimation-based Anomaly Detection
  2.5 Principal Component Analysis
  2.6 Kernel Principal Component Analysis
  2.7 Normalized Compression Distance-based Similarity Metric
 3. Experiments
  3.1 Data
  3.2 Results
 4. Conclusion and Future Directions
 References

저자정보

  • Tarem Ahmed Department of Electrical & Electronic Engineering BRAC University Dhaka, Bangladesh
  • Supriyo Ahmed Department of Electrical & Electronic Engineering BRAC University Dhaka, Bangladesh
  • Al-Sakib Khan Pathan Department of Computer Science International Islamic University Malaysia Kuala Lumpur, Malaysia

참고문헌

자료제공 : 네이버학술정보

    함께 이용한 논문

      ※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

      0개의 논문이 장바구니에 담겼습니다.