Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników

Znaleziono wyników: 2

Liczba wyników na stronie
first rewind previous Strona / 1 next fast forward last
Wyniki wyszukiwania
Wyszukiwano:
w słowach kluczowych:  scale space
help Sortuj według:

help Ogranicz wyniki do:
first rewind previous Strona / 1 next fast forward last
1
Content available remote Pedestrian Detection and Analysis with Scale-Space and Distance Transform
EN
Because the amount of various video streams recorded by video surveillance systems is increasing, the new approach, where human operator analyzing the video is replaced by artificial intelligence system is gaining new followers. The algorithm have to meet several requirements: must be accurate and not produce too many false alarms, moreover it must be able to process the received video stream in real-time to provide sufficient response time. In the article a system is presented which is able to detect and analyze walking pedestrians. It is based on two algorithms: scale space and matching contours using distance transform. The information can be used by other parts of the advanced video surveillance system, namely object tracking by detection, detecting heavy equipment only zone intrusion or for sorting out possible suspicious persons (pickpocket, homeless etc.).
EN
The aim of the proposed watershed based image segmentation technique is to split images into spatially homogeneous regions, which can be further processed by different image analysis tools. The advantage of such approach, in comparison to pixel oriented processing, is its lower sensitivity to superimposed noise due to averaging of regions properties over their area. The watershed segmentation technique is based on interpretation of an image as a topographic relief and on simulation of flow of water along steepest descent paths called downstreams. Thus, for each local minimum of the image, a drainage region is defined, which, if computed for a gradient image, represents an area with approximately constant properties. The segmentation technique is further extended for multi-scale image analysis by means of Gaussian smoothing. The aim of smoothing is to suppress image details that are smaller than standard deviation of the Gaussian. However, smoothing results not only in the desired increase of region size, but it also affects position of region boundaries, at least for larger standard deviations of the Gaussian filter. Therefore a new technique is proposed, based on region hierarchies, which enables to transfer region contours with precise position from the levels with low smoothing to levels with higher smoothing. Thus, segmentation of an image into large regions, but with exact contours, is obtained.
first rewind previous Strona / 1 next fast forward last
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.