Details

Autor(en) / Beteiligte

• Arif, O.
• Vela, P.A.

Titel

Kernel covariance image region description for object tracking

Ist Teil von

• 2009 16th IEEE International Conference on Image Processing (ICIP), 2009, p.865-868

Ort / Verlag

IEEE

Erscheinungsjahr

2009

Quelle

IEEE Electronic Library (IEL)

Beschreibungen/Notizen

• We propose a nonlinear covariance region descriptor for target tracking. The target object appearance and spatial information is represented using a covariance matrix in a target derived Hilbert space using kernel principal component analysis. A similarity measure is derived, which computes the similarity of a candidate image region to the learned covariance matrix. A variational technique is provided to maximize the similarity measure, which iteratively finds the best matched object region. Tracking performance is demonstrated on a variety of sequences containing noise, occlusions, illumination changes, background clutter, etc.