Earlier spatial orientation studies used both motion-detection (e.g., did I move?) and direction-recognition (e.g., did I move left/right?) paradigms. The purpose of our study was to compare thresholds measured with motion-detection and direction-recognition tasks on a standard Moog motion platform to see whether a substantial fraction of the reported threshold variation might be explained by t...

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...

Design of automated video surveillance systems is one of the exigent missions in computer vision community because of their ability to automatically select frames of interest in incoming video streams based on motion detection. This research paper focuses on the real-time hardware implementation of a motion detection algorithm for such vision based automated surveillance systems. A dedicated VL...

This paper presents a new method for extracting semantic information from basketball video. Our approach consists of three stages: shot and scene boundary detection, scene classification and semantic video analysis for event detection. The scene boundary detection algorithm is based on both visual and motion prediction information. After the shot and scene boundary detection, a set of visual an...

Motion detection can be achieved either with mechanisms sensitive to a target's velocity, or sensitive to change in a target's position. Using a procedure to dissociate these two provided by Nakayama and Tyler (Vis Res 1981;21:427-433), we explored detection of first-order (luminance-based) and various second-order (texture-based and stereo-based) motion. In the first experiment, observers view...

Often it is claimed that humans are particularly sensitive to biological motion. Here, sensitivity as a detection advantage for biological over nonbiological motion is examined. Previous studies comparing biological motion to nonbiological motion have not used appropriate masks or have not taken into account the underlying form present in biological motion. The studies reported here compare the...

The human contrast sensitivity function is bandpass in form for stimuli of low temporal frequency but low pass for flickering or moving stimuli. Because the loss in sensitivity to moving stimuli is large, images moving on the retina have little perceptible high-spatial-frequency content. The loss of high-spatial-frequency content--often referred to as motion blur--provides a potential cue to mo...

We present new probabilistic motion models of interest for the detection of meaningful dynamic contents (or events) in videos. We separately handle the dominant image motion assumed to be due to the camera motion and the residual image motion related to scene motion. These two motion components are then represented by different probabilistic models which are further recombined for the event det...

The aim of this paper is a comparative analysis of methods for motion detection and human recognition in the image. Authors propose the own solution following the comparative analysis of current approaches. Then authors design and implement hardware and software solution for motion detection in the video with human recognition in the picture. The development board Intel Galileo serves as the ba...