Abstract
In this paper, an iterative tracking algorithm based on a non-linear JTC (Joint Transform Correlator) architecture and enhanced
by a digital image processing method is proposed and validated. This algorithm is based on the computation of a
correlation plane where the reference image is updated at each frame. For that purpose, we use the JTC technique in real
time to track a patient (target image) in a room fitted with a video camera. The correlation plane is used to localize the
target image in the current video frame (frame i). Then, the reference image to be exploited in the next frame (frame i+1)
is updated according to the previous one (frame i). In an effort to validate our algorithm, our work is divided into two parts:
(i) a large study based on different sequences with several situations and different JTC parameters is achieved in order to
quantify their effects on the tracking performances (decimation, non-linearity coefficient, size of the correlation plane, size
of the region of interest...). (ii) the tracking algorithm is integrated into an application of elderly fall detection. The first
reference image is a face detected by means of Haar descriptors, and then localized into the new video image thanks to our
tracking method. In order to avoid a bad update of the reference frame, a method based on a comparison of image intensity
histograms is proposed and integrated in our algorithm. This step ensures a robust tracking of the reference frame. This
article focuses on face tracking step optimisation and evalutation. A supplementary step of fall detection, based on vertical
acceleration and position, will be added and studied in further work.
