Accession Number:

ADA533086

Title:

Robust Kernel-Based Object Tracking with Multiple Kernel Centers

Descriptive Note:

Conference paper

Corporate Author:

CONNECTICUT UNIV STORRS DEPT OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCE

Personal Author(s):

Report Date:

2009-07-09

Pagination or Media Count:

9.0

Abstract:

Visual tracking in the real world is challenging with unavoidable background interference, target orientation variations and scale changes. Spatial information needs to be exploited to increase robustness however, current methods such as Spatiogram suffer from the large complexity of spatial covariance calculation. Recently, joint distribution representation has been used to estimate target orientation and scale, but this representation is at the expense of losing position localization information. A new framework is proposed for target model representation by employing multiple kernel centers MKC within the kernel window. By employing MKC, spatial information is implicitly embedded. Steepest gradient ascent is used to track the target position, orientation and scale simultaneously. Using an adaptive stepsize in the gradient ascent iteration, the proposed method inherits the desirable properties of the mean shift approach and shows a fast convergence rate. The experimental results in several challenging scenarios demonstrate its robustness and superiority to previous technique.

Subject Categories:

  • Numerical Mathematics
  • Target Direction, Range and Position Finding

Distribution Statement:

APPROVED FOR PUBLIC RELEASE