In this work, a correlation-based algorithm consisting of a set of adaptive filters for
recognition of occluded objects in still and dynamic scenes in the presence of additive noise …

Correlation filters for target detection are usually designed by analytical optimization of
performance criteria. The resulting expressions require explicit knowledge about the …

Design of conventional correlation filters requires explicit knowledge of the appearance and
shape of a target object, so the performance of correlation filters is significantly affected by …

We present the design of correlation filters for detection of a target in a noisy input scene
when the object of interest is given in a noisy reference image. The target signal, shape and …

Tracking solves the problem of detecting and estimating the future target state in an input
video sequence. In this work, an adaptive tracking algorithm by means of multiple object …

Correlation filters for pattern recognition are commonly designed under the assumption that
the shape and appearance of an object of interest are explicitly known. In this paper, we …

A tracking algorithm using locally adaptive correlation filtering is proposed. The algorithm is
designed to track multiple objects with invariance to pose, occlusion, clutter, and illumination …

An algorithm for tracking of multiple objects in video based on time-adjustable adaptive
composite correlation filtering is proposed. For each frame a bank of composite correlation …

In recent years tracking applications with development of new technologies like smart TVs,
Kinect, Google Glass and Oculus Rift become very important. When tracking uses a …

Correlation filters used for object detection are commonly designed using explicit knowledge
of the target appearance and the target shape. This assumption requires that the image of a …