Object of interest detection in video sequence using co-segmentation: A new era in video surveillance

2018 ◽  
Author(s):  
Sanmoy Bandyopadhyay
Keyword(s):  
Video Surveillance ◽  
Video Sequence ◽  
New Era ◽  
Interest Detection

Human Detection by Surveillance Camera

2018 ◽  
Vol 6 (1) ◽  
pp. 21-33
Author(s):  
Larbi Guezouli ◽  
Hanane Boukhetache ◽  
Imene Kebi
Keyword(s):  
Video Surveillance ◽  
Surveillance System ◽  
Video Sequence ◽  
Rapid Development ◽  
Human Detection ◽  
Video Surveillance System ◽  
Surveillance Systems ◽  
Considerable Time ◽  
Surveillance Camera ◽  
Analytical Tools

Security problems and decreasing costs, leads to the rapid development of video surveillance systems. It is necessary to implement analytical tools capable of identifying objects that may appear in the video sequence. The work presented in this article consists of designing a video surveillance system for the automatic detection of humans in a video sequence acquired by a fixed camera. The principle of this work is based on the modeling and subtraction of the background. In order to determine the nature of the objects, the authors make the detection of the contours of the foreground image, then by matching this contour with the images of a base, silhouette images of people in different positions. The acquisition of the frames is carried out in real time, the matching of the images takes a considerable time and this time becomes increasingly longer based on the size of the base. To solve this problem, the authors have used the parallelism.

scholarly journals Proposed System of Enhancement in Accuracy for Fire Detection System using Machine Learning Algorithm

2020 ◽  
Vol 9 (4) ◽  
pp. 2093-2097
Keyword(s):  
Video Surveillance ◽  
Video Sequence ◽  
Learning Algorithm ◽  
Detection System ◽  
Early Stage ◽  
Fire Detection ◽  
Early Event ◽  
Generation System ◽  
Fire Event ◽  
Better Than

The video surveillance system has become a important part in the security and protection of cities. The Video surveillance has become an important factor in the cities, since smart monitoring cameras mounted with intelligent video analytics techniques can monitor and pre-alert system by capturing abnormal activity such as fire events. The current world is completely under CCTV for make the various areas secure. The video recorded is unable to find out fire detection at early stage of fire event. After event happened this video sequence is used to find out causes of an event/fire but problem is after event happened system are unable to save loss by that event or accident, so there is need to such system is able to help us in early event detection and pre-alert generation system. Motive behind this proposed work is to invent pre-alert generation system without any hardware as well as sensor. Accuracy of this proposed system may be approx.85-90% or more which is better than existing system.

scholarly journals Computer simulation of adapting the object image selection method to video surveillance conditions

2021 ◽  
Vol 2052 (1) ◽  
pp. 012021
Author(s):  
N P Kornyshev ◽  
D A Serebrjakov
Keyword(s):  
Computer Simulation ◽  
Video Surveillance ◽  
Video Sequence ◽  
Selection Method ◽  
Local Contrast ◽  
Special Cases ◽  
Correct Determination ◽  
Uniform Background ◽  
Object Parameters

Abstract The article deals with the issues of computer modeling of methods for selecting images of objects against a non-uniform background. A test video sequence with given background and object parameters is considered, which provides imitation of one of the special cases of video surveillance conditions, namely, the convergence of the video surveillance point and the object. The issues of adaptation of the compensation selection method to the specified conditions of video surveillance are discussed. Examples of test images and graphs of dependences of the probability of correct determination of coordinates depending on the value of the local contrast of the object in relation to the background, obtained by computer simulation are given.

scholarly journals Abnormality Detection Using LBP Features and K-Means Labelling based Feed-Forward Neural Network in Video Sequence

2019 ◽  
Vol 8 (9S) ◽  
pp. 629-633
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Video Surveillance ◽  
Local Binary Pattern ◽  
Video Sequence ◽  
Detection Method ◽  
Experimental Results ◽  
Abnormality Detection ◽  
Feed Forward Neural Network ◽  
Feed Forward

Video surveillance is widely used in various domains like military, commercial and consumer areas. One of the objectives in video surveillance is the detection of normal and abnormal behavior.It has always been a challenge to accurately identify such events in any real time video sequence. In this paper, abnormality detection method using Local Binary Pattern and k-means labeling basedfeed-forward neural network has been proposed. The performance of the proposed method has also been compared with four other techniques in literature to show its worthiness. It can be seen in the experimental results that an accuracy of up to 98% has been achieved for the proposed technique.

scholarly journals A 3D Approach to Co-Occurrence Matrix Features Used in Dynamic Textures Indexing

2013 ◽  
Vol 8-9 ◽  
pp. 516-526 ◽  
Author(s):  
Muguras Mocofan ◽  
Vasiu Radu
Keyword(s):  
Video Surveillance ◽  
Video Sequence ◽  
Medical Application ◽  
Dynamic Texture ◽  
Dynamic Textures ◽  
Temporal Features ◽  
Large Databases ◽  
3D Matrix ◽  
Indexing Model ◽  
Occurrence Matrix

The area of applications of dynamic texture is increasingly wide: video surveillance, transaction systems, medical application and video synthesis. The paper presents an indexing model in large databases of dynamics texture using the co-occurrence matrix features. The data from the video sequence that represents the dynamic texture are loaded in a 3D matrix. The application of the co-occurrence matrix is performed for each frame of the data parallelepiped covered in 3 directions. This enables/facilitates the integration of the temporal features of the dynamic texture in the mathematical description of the behaviour. Additionally, we use more translations to compute the indexing vector from the 2D+T space of dynamic textures.

scholarly journals ESTIMATION OF THE CROSS CORRELATION BASED OPTICAL FLOW FOR VIDEO SURVEILLANCE

2014 ◽  
pp. 112-117
Author(s):  
Rauf Sadykhov ◽  
Denis Lamovsky
Keyword(s):  
Optical Flow ◽  
Video Surveillance ◽  
Cross Correlation ◽  
Video Sequence ◽  
Correlation Coefficients ◽  
General Purpose ◽  
Video Sequences ◽  
Flow Estimation ◽  
Optical Flow Estimation ◽  
Filtering Technique

This paper describes a new algorithm to calculate cross-correlation function. We combined box filtering technique for calculation of cross correlation coefficients with parallel processing using MMX/SSE technology of modern general purpose processors. We have used this algorithm for real time optical flow estimation between frames of video sequence. Our algorithm was tested on real world video sequences obtained from the cameras of video surveillance system.

Unbiased estimation of particle number and sizes using the new stereological tools: the disector, the fractionator, the selector, and the nucleator — or just point-sampled intercepts

1988 ◽  
Vol 46 ◽  
pp. 428-429
Author(s):  
H.J.G. Gundersen
Keyword(s):  
Particle Number ◽  
Small Distance ◽  
Parallel Plane ◽  
Unbiased Estimation ◽  
Severe Problem ◽  
New Era ◽  
Size And Shape ◽  
Distinct Property ◽  
Sectioned Tissue

Previously, all stereological estimation of particle number and sizes were based on models and notoriously gave biased results, were very inefficient to use and difficult to justify. For all references to old methods and a direct comparison with unbiased methods see recent reviews.The publication in 1984 of the DISECTOR, the first unbiased stereological probe for sampling and counting 3—D objects irrespective of their size and shape, signalled the new era in stereology — and give rise to a number of remarkably simple and efficient techniques based on its distinct property: It is the only known way to obtain an unbiased sample of 3-D objects (cells, organelles, etc). The principle is simple: within a 2-D unbiased frame count or sample only cells which are not hit by a parallel plane at a known, small distance h.The area of the frame and h must be known, which might sometimes in itself be a problem, albeit usually a small one. A more severe problem may arise because these constants are known at the scale of the fixed, embedded and sectioned tissue which is often shrunken considerably.

Drug Induced Changes in Cell Organelles

1968 ◽  
Vol 26 ◽  
pp. 110-111
Author(s):  
Sarah A. Luse
Keyword(s):  
Clinical Medicine ◽  
Cell Organelles ◽  
Riboflavin Deficiency ◽  
Drug Induced ◽  
New Era ◽  
Health And Disease ◽  
In The Beginning ◽  
Cellular Pathology ◽  
Induced Changes ◽  
The Impact

In the mid-nineteenth century Virchow revolutionized pathology by introduction of the concept of “cellular pathology”. Today, a century later, this term has increasing significance in health and disease. We now are in the beginning of a new era in pathology, one which might well be termed “organelle pathology” or “subcellular pathology”. The impact of lysosomal diseases on clinical medicine exemplifies this role of pathology of organelles in elucidation of disease today.Another aspect of cell organelles of prime importance is their pathologic alteration by drugs, toxins, hormones and malnutrition. The sensitivity of cell organelles to minute alterations in their environment offers an accurate evaluation of the site of action of drugs in the study of both function and toxicity. Examples of mitochondrial lesions include the effect of DDD on the adrenal cortex, riboflavin deficiency on liver cells, elevated blood ammonia on the neuron and some 8-aminoquinolines on myocardium.

Belimumab's Approval Marks New Era for Lupus

2011 ◽  
Vol 10 (4) ◽  
pp. 9
Author(s):  
MITCHEL L. ZOLER
Keyword(s):  
New Era

Supervision for a New Era

1971 ◽  
Vol 16 (9) ◽  
pp. 556-558
Author(s):  
KEVIN RYAN
Keyword(s):  
New Era
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