BACKGROUND Tracking moving objects in space is important for the maintenance of spatiotemporal continuity in everyday visual tasks. In the laboratory, this ability is tested using the Multiple Object Tracking (MOT) task, where participants track a subset of moving objects with attention over an extended period of time. The ability to track multiple objects with attention is severely limited. Re...

Due to the capture process, video signals are generally contaminated by noise. Furthermore, overall video quality can be improved by reducing sharpness in fast moving areas, except in cases where the eye is able to track the motion. In this paper we propose a relatively simple pre-processing method that is able to address both these situations. The proposed pre-processing algorithm is based on ...

The paper describes an approach to vehicle detection and tracking fully based on the Block Matching Algorithm (BMA), which is the motion estimation algorithm employed in the MPEG compression standard. BMA partitions the current frame in small, fixed size blocks and matches them in the previous frame in order to estimate blocks displacement (referred to as motion vectors) between two successive ...

We propose an object-tracking algorithm that predicts the object contour using motion vector information. Tracking is achieved by predicting the object boundary using motion vectors, followed by contour update, using occlusions/disocclusion detection. An adaptive block-based approach has been used for estimating motion between frames. An efficient modulation scheme is used to control the gap be...

Introduction The image quality of brain MRI scans can be compromised by head motion. Prospective motion correction based on external tracking systems has been proposed to ameliorate this issue. Stereo optical tracking systems have been shown to give good real-time motion correction with reasonable accuracy [1,2]. However, the accurate calibration for the stereo system as well as the calibration...

Motion detection is a basic operation in the selection of significant segments of the video signals. For an effective Human Computer Intelligent Interaction, the computer needs to recognize the motion and track the moving object. Here an efficient neural network system is proposed for motion detection from the static background. This method mainly consists of four parts like Frame Separation, R...

The appearance of moving features in the field-of-view (FoV) of the camera may substantially change due to different camera poses. Typical solutions for tracking image points involve the assumption of an image motion model and the estimation of the motion parameters using image alignment techniques. While for conventional cameras this suffices, the radial distortion that arises in cameras with ...