Robust 3D Surveillance

Abstract

Major Goals: 1. Robustness of 3D data sensed by LiDAR (Light Detection and Ranging) cameras. LiDAR cameras have longer range for sensing and provide data for applications in multiple fields such as self-driving cars, geography mapping (that can be used for surveillance as well). We will carry out anti-forensic and forensic studies on LiDAR data using the STIR funding. The preliminary results from this study will help us address the concern expressed by the reviewer (for the earlier proposals focus on using only Microsofts Kinect data). 2. Real-time Performance of Multi-camera 3D Meshing We will also employ the STIR funding to get preliminary results on real-time performance of 3D reconstruction approaches. As mentioned earlier, we have been able to achieve real-time performance by working in the depth image domain, and mapping it back to the 3D. We will continue with our efforts and get additional preliminary results to show the feasibility for handling multiple camera data. Accomplishments: 1. For RGB-D cameras, we first presented a real-time anti-forensic 3D object stream manipulation framework to capture and manipulate live RBG-D data streams to create realistic images/videos showing individuals performing activities they did not actually do. The framework uses computer vision and graphics methods to render photo-realistic animations of live mesh models captured using the camera. Next, we conducted a visual inspection of the manipulated RGB-D streams (just like security personnel would do) by users who are computer vision and graphics scientists. The study shows that it was significantly difficult to distinguish between the real or reconstructed rendering of such 3D video sequences, thus clearly showing the potential security risk involved. Finally, we investigated the efficacy of forensic approaches for detecting such manipulations.

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Document Details

Document Type
Technical Report
Publication Date
Apr 30, 2017
Accession Number
AD1081708

Entities

People

  • Balakrishnan Prabhakaran

Organizations

  • University of Texas at Dallas

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Engineered Resilient Systems
  • Human Systems
  • Sensors

DTIC Thesaurus Topics

  • Accumulators
  • Accuracy
  • Additives (Chemicals)
  • Algorithms
  • Computer Vision
  • Computers
  • Coordinate Systems
  • Detection
  • Detectors
  • Images
  • Lidar
  • Point Clouds
  • Security Personnel
  • Students
  • Surveillance
  • Two Dimensional
  • Unmanned Vehicles

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Distributed Systems and Data Platform Development

Technology Areas

  • AI & ML