Stationary target detection using the objectvideo surveillance system

Venetianer, P.L.; Zhang, Z.; Yin, Weihong; Lipton, A.J.

doi:10.1109/avss.2007.4425317

Cited by 48 publications

(21 citation statements)

References 14 publications

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“…In order to compare our results with those obtained by other researchers such as [8], [9], [10], [11], [12] and [16], our method has also been tested using the sample i-LIDS subset. …”

Section: B Results On I-lids Sample Data Setmentioning

confidence: 87%

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Detection of Parked Vehicles Using Spatiotemporal Maps

Albiol

Sanchis

Albiol

et al. 2011

IEEE Trans. Intell. Transport. Syst.

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This paper presents a video-based approach to detect the presence of parked vehicles in street lanes.Potential applications include detection of illegally and double-parked vehicles in urban scenarios and incident detection on roads. The technique extracts information from low-level feature points (Harris corners) in order to create spatio-temporal maps that describe what is happening in the scene.The method does not rely on any background subtraction or perform any form of object tracking.The system has been evaluated using private and public data sets and has proven to be robust against common difficulties found in CCTV video such as varying illumination, camera vibration, presence of momentary occlusion by other vehicles, and high noise levels.

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“…In order to compare our results with those obtained by other researchers such as [8], [9], [10], [11], [12] and [16], our method has also been tested using the sample i-LIDS subset. …”

Section: B Results On I-lids Sample Data Setmentioning

confidence: 87%

“…Examples of algorithms that use background subtraction and object tracking include [8], [9], [10], [11], [12], [13]. For instance, in [8], Bevilacqua and Vaccari present a method to detect stopped vehicles based on the detection of the tracked object's centroid position during short time intervals.…”

Section: Previous Workmentioning

confidence: 99%

Detection of Parked Vehicles Using Spatiotemporal Maps

Albiol

Sanchis

Albiol

et al. 2011

IEEE Trans. Intell. Transport. Syst.

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“…The method described in (Venetianer et al, 2005) uses interesting point detection based object tracking methods and measures of salience that are not related to the parabolic trajectories of falling objects.…”

Section: Related Workmentioning

confidence: 99%

Detecting Objects Thrown over Fence in Outdoor Scenes

Csordás

Havasi

Szirányi

2015

Proceedings of the 10th International Conference on Computer Vision Theory and Applications

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Abstract:We present a new technique for detecting objects thrown over a critical area of interest in a video sequence made by a monocular camera. Our method was developed to run in real time in an outdoor surveillance system. Unlike others, we use an optical flow based motion detection and tracking system to detect the object's trajectories and for parabolic path search. The system successfully detects thrown objects of various sizes and is unaffected by the rotation of the objects.

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“…A classical distinctions consist of their purpose: they can be divided into generic and specialized. For instance, [38] proposed a framework for the video surveillance domain and [41] focused on the detection of stationary objects in underground stations. Another classication dierentiates between distributed [25] and nondistributed frameworks [36].…”

Section: Characteristics Of Video Event Analysis Frameworkmentioning

confidence: 99%