Abstract-Papers up to 4 pages should be submitted using this format

II. EXTRACTION OF TEMPORAL MOTOR ACTIVITY SIGNALS FROM VIDEO Abstract—This paper presents a new method for tracking features in video. This method estimates the displacement of a feature between two successive frames by minimizing an error function defined in terms of the feature intensities at these frames. Feature tracking relies on a rigid motion model, which allows for translation, rotation and uniform scaling of the feature tracked from one frame to the next. The proposed feature tracking method is used to extract motor activity signals from video recordings of neonatal seizures. Figure 1 illustrates the mechanism that can be used for generating temporal signals tracking the movements of different parts of the infant’s body during focal clonic and myoclonic seizures [4]. Figure 1 depicts a single frame containing the sketch of an infant’s body with four selected anatomical sites. In this particular configuration, XLL and YLL represent the projections of the site located at the left leg to the horizontal and vertical axes, respectively. The projections of the sites located at the right leg, left hand, and right hand are denoted by XRL and YRL, XLH and YLH, and XRH and YRH, respectively. As the infant moves its extremities, the locations of the sites in the frame will change, as will the projections of the sites to the horizontal and vertical axes. Recording the values of the projections from frame to frame of the videotaped seizure will generate four pairs of temporal signals, namely the signals XLL(t) and YLL(t) for the left leg, the signals XRL(t) and YRL(t) for the right leg, the signals XLH(t) and YLH(t) for the left hand, and the signals XRH(t) and YRH(t) for the right hand. For a given set of anatomical sites, each seizure will produce signature signals depending on its type and location. Keywords—Feature tracking, motor activity signal, rigid motion, rotation, scaling