PlumX Metrics
Embed PlumX Metrics

Query-Based Multiview Detection for Multiple Visual Sensor Networks

Sensors, ISSN: 1424-8220, Vol: 24, Issue: 15
2024
  • 0
    Citations
  • 0
    Usage
  • 2
    Captures
  • 2
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Captures
    2
  • Mentions
    2
    • Blog Mentions
      1
      • Blog
        1
    • News Mentions
      1
      • 1

Most Recent News

University of Washington Researcher Reports on Findings in Sensor Research (Query-Based Multiview Detection for Multiple Visual Sensor Networks)

2024 AUG 13 (NewsRx) -- By a News Reporter-Staff News Editor at Tech Daily News -- Fresh data on sensor research are presented in a

Article Description

In IoT systems, the goal of multiview detection for multiple visual sensor networks is to use multiple camera perspectives to address occlusion challenges with multiview aggregation being a crucial component. In these applications, data from various interconnected cameras are combined to create a detailed ground plane feature. This feature is formed by projecting convolutional feature maps from multiple viewpoints and fusing them using uniform weighting. However, simply aggregating data from all cameras is not ideal due to different levels of occlusion depending on object positions and camera angles. To overcome this, we introduce QMVDet, a new query-based learning multiview detector, which incorporates an innovative camera-aware attention mechanism for aggregating multiview information. This mechanism selects the most reliable information from various camera views, thus minimizing the confusion caused by occlusions. Our method simultaneously utilizes both 2D and 3D data while maintaining 2D–3D multiview consistency to guide the multiview detection network’s training. The proposed approach achieves state-of-the-art accuracy on two leading multiview detection benchmarks, highlighting its effectiveness for IoT-based multiview detection scenarios.

Bibliographic Details

Hsu, Hung-Min; Yuan, Xinyu; Chuang, Yun-Yen; Sun, Wei; Chang, Ray-I

MDPI AG

Chemistry; Computer Science; Physics and Astronomy; Biochemistry, Genetics and Molecular Biology; Engineering

Provide Feedback

Have ideas for a new metric? Would you like to see something else here?Let us know