Autonomous tracking of vehicle taillights from a mobile platform using an embedded smart camera

Akhan Almagambetov, Mauricio Casares, Senem Velipasalar

Research output: Chapter in Book/Entry/PoemConference contribution

1 Scopus citations

Abstract

The detection and tracking of vehicle taillights is an important aspect of collision avoidance systems and autonomous vehicle applications. In this paper, we present a novel and efficient algorithm for tracking the vehicle taillights from a mobile platform, under both daytime and nighttime conditions, which is entirely implemented on a CITRIC embedded smart camera. The algorithm uses a Kalman filter and a codebook to achieve a high level of robustness. On the microprocessor of the camera, it takes about 177 ms to process one frame of live camera data (which translates to approximately 6 fps). We demonstrate lightweight and reliable tracking of vehicle taillights, despite foreign objects appearing in view, blocking the view, or the vehicle changing lanes. In all of these cases, the algorithm is able to gracefully recover and resume normal operation. We will use this system as an initial platform for implementing other functionality, such as the detection of vehicle alert signals (brakes, turn signals, emergency flashers), which is also discussed. Compared to most existing work that focuses only on nighttime detection, the proposed algorithm provides daytime tracking of taillights, which is inherently more challenging.

Original languageEnglish (US)
Title of host publication2012 6th International Conference on Distributed Smart Cameras, ICDSC 2012
StatePublished - 2012
Event2012 6th International Conference on Distributed Smart Cameras, ICDSC 2012 - Hong Kong, China
Duration: Oct 30 2012Nov 2 2012

Publication series

Name2012 6th International Conference on Distributed Smart Cameras, ICDSC 2012

Other

Other2012 6th International Conference on Distributed Smart Cameras, ICDSC 2012
Country/TerritoryChina
CityHong Kong
Period10/30/1211/2/12

Keywords

  • Embedded software
  • Kalman filter
  • autonomous vehicles
  • cameras
  • signal processing algorithms
  • tracking
  • transportation
  • vehicle light detection

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials

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