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Proceedings Paper

Real-time vehicle detection and tracking based on perspective and non-perspective space cooperation
Author(s): Jon Arróspide; Luis Salgado; Marcos Nieto; Fernando Jaureguizar
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Paper Abstract

In recent years advanced driver assistance systems (ADAS) have received increasing interest to confront car accidents. In particular, video processing based vehicle detection methods are emerging as an efficient way to address accident prevention. Many video-based approaches are proposed in the literature for vehicle detection, involving sophisticated and costly computer vision techniques. Most of these methods require ad hoc hardware implementations to attain real-time operation. Alternatively, other approaches perform a domain change --via transforms like FFT, inverse perspective mapping (IPM) or Hough transform-- that simplifies otherwise complex feature detection. In this work, a cooperative strategy between two domains, the original perspective space and the transformed non-perspective space computed trough IPM, is proposed in order to alleviate the processing load in each domain by maximizing the information exchange between the two domains. A system is designed upon this framework that computes the location and dimension of the vehicles in a video sequence. Additionally, the system is made scalable to the complexity imposed by the scenario. As a result, real-time vehicle detection and tracking is accomplished in a general purpose platform. The system has been tested for sequences comprising a wide variety of scenarios, showing robust and accurate performance.

Paper Details

Date Published: 4 February 2009
PDF: 12 pages
Proc. SPIE 7244, Real-Time Image and Video Processing 2009, 72440H (4 February 2009); doi: 10.1117/12.812253
Show Author Affiliations
Jon Arróspide, Univ. Politécnica de Madrid (Spain)
Luis Salgado, Univ. Politécnica de Madrid (Spain)
Marcos Nieto, Univ. Politécnica de Madrid (Spain)
Fernando Jaureguizar, Univ. Politécnica de Madrid (Spain)


Published in SPIE Proceedings Vol. 7244:
Real-Time Image and Video Processing 2009
Nasser Kehtarnavaz; Matthias F. Carlsohn, Editor(s)

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