| Titre : | Setting up a software for computer vision algorithms applied to video streams | | Type de document : | projet fin études | | Auteurs : | NOUFAIL Nassima, Auteur | | Langues : | Anglais (eng) | | Catégories : | Ingénierie de web et Informatique mobile
| | Mots-clĂ©s : | Video analysis, Computer Vision, tracking people, monitoring, surveillance video, low resolution, motion analysis, pattern recognition. | | Index. dĂ©cimale : | 1933/18 | | RĂ©sumĂ© : | Digital videos have been more used in the past few years in different fields and that’s why many researchers are doing to enhance this technology.
Actually, Video analysis is a field within computer vision that involves the automatic interpretation of digital video using computer vision algorithms. Although humans are readily able to interpret digital videos, developing algorithms for the computer to perform the same task has been highly evasive and is now an active research field. Applications include tracking people who are walking; interpreting actions of moving objects and people; and using the technology to replace the array of screens used in monitoring high-risk environments. In this project, our goal is to provide a software solution for Texas Department of Public Safety TxPSD that allows the department to have more sufficient algorithms for analyzing videos taking by surveillance cameras in all the state of Texas. The usual problem for this kind of algorithms is to locate people in an image or video sequence, different approaches had been found by researchers in the past decade, many of them are considering the human detection as a difficult task from a machine vision perspective as it is influenced by a wide range of possible appearance due to changing articulated pose, clothing, lighting and background, but prior knowledge of these limitations can improve the detection performance.
The scenes obtained from the different camera surveillance are with different resolution. Most of the scenes captured by the static camera are with minimal change of background. Objects in the outdoor surveillance are often detected in the far field. Most existing digital video surveillance systems rely on human observers for detecting specific activities in a real-time video scene. However, there are limitations in the human capability to monitor simultaneous events in surveillance displays. Hence, human motion analysis in automated video surveillance has become one of the most active and attractive research topics in the area of computer vision and pattern recognition.
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Setting up a software for computer vision algorithms applied to video streams [projet fin études] / NOUFAIL Nassima, Auteur . - [s.d.]. Langues : Anglais ( eng) | Catégories : | Ingénierie de web et Informatique mobile
| | Mots-clĂ©s : | Video analysis, Computer Vision, tracking people, monitoring, surveillance video, low resolution, motion analysis, pattern recognition. | | Index. dĂ©cimale : | 1933/18 | | RĂ©sumĂ© : | Digital videos have been more used in the past few years in different fields and that’s why many researchers are doing to enhance this technology.
Actually, Video analysis is a field within computer vision that involves the automatic interpretation of digital video using computer vision algorithms. Although humans are readily able to interpret digital videos, developing algorithms for the computer to perform the same task has been highly evasive and is now an active research field. Applications include tracking people who are walking; interpreting actions of moving objects and people; and using the technology to replace the array of screens used in monitoring high-risk environments. In this project, our goal is to provide a software solution for Texas Department of Public Safety TxPSD that allows the department to have more sufficient algorithms for analyzing videos taking by surveillance cameras in all the state of Texas. The usual problem for this kind of algorithms is to locate people in an image or video sequence, different approaches had been found by researchers in the past decade, many of them are considering the human detection as a difficult task from a machine vision perspective as it is influenced by a wide range of possible appearance due to changing articulated pose, clothing, lighting and background, but prior knowledge of these limitations can improve the detection performance.
The scenes obtained from the different camera surveillance are with different resolution. Most of the scenes captured by the static camera are with minimal change of background. Objects in the outdoor surveillance are often detected in the far field. Most existing digital video surveillance systems rely on human observers for detecting specific activities in a real-time video scene. However, there are limitations in the human capability to monitor simultaneous events in surveillance displays. Hence, human motion analysis in automated video surveillance has become one of the most active and attractive research topics in the area of computer vision and pattern recognition.
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Setting up a software for computer vision algorithms applied to video streams / NOUFAIL Nassima
