scholarly journals Face Detection and Recognition for use in Campus Surveillance

The study of image processing in today’s world and the booming possibility of building a smart classroom and a smarter campus with the help of aided vigilance and surveillance is slowly moving from a thought that can be considered for the future to an actual real-world implementation. In modern day schools and university campuses there is an increasing demand for a real-time monitoring and quick responding database that tracks the student activities. This is not always required but serves as a one-click system that handles average information searches and returns the list of fast action options that are available in tracking the campus activities that come in the purview of its span. In a diverse educational campus comprising of several branches and streams that share a single campus, there is a possible chance of intrusion and unauthorized entry which may lead to undesirable and unnecessary loss of intellectual property and manipulation of identity. In a particular academic unit, there would be a surveillance system that monitors and tracks these activities and offers to its privileged users a response in real-time. It can also be used to track the attendance of students in an automated fashion which leads to a digitized and paperless approach. It can be said that this will be implemented in its entirety to a campus unit. Face identification is an essential step in face recognition, in which one of the typical of a class and authoritative application in visual sensor network. Visual perception is one of the physical measurements based on secured features. Face identification is a demanding assignment, because it has to scan and match against a library of known faces. E.g. lighting condition, different posture, various kind of body languages.

2013 ◽  
Vol 36 (1) ◽  
pp. 409-419 ◽  
Author(s):  
M. Hooshmand ◽  
S.M.R. Soroushmehr ◽  
P. Khadivi ◽  
S. Samavi ◽  
S. Shirani

2013 ◽  
Vol 303-306 ◽  
pp. 187-190
Author(s):  
Lei You ◽  
Xin Su ◽  
Yu Tong Han

Wireless visual sensor network (WVSN) is emerging with many potential applications. The lifetime of a WVSN is seriously dependent on the energy shored in the battery of its sensor nodes as well as the adopted compression and resource allocation scheme. In this paper, we use the energy harvesting to provide almost perpetual operation of the networks and compressed-sensing-based encoding to decrease the power consumption of acquiring visual information at the front-end sensors. We propose a dynamic algorithm to jointly allocate power for both compressive-sensing-based visual information acquisition and data transmission, as well as the available bandwidth under energy harvesting and stability constraints. A virtual energy queue is introduced to control the resource allocation and the measurement rate in each time slot. The algorithm can guarantee the stability of the visual data queues in all sensors and achieve near-optimal performance.


2018 ◽  
Vol 14 (8) ◽  
pp. 155014771879380
Author(s):  
Gang Cao ◽  
Huawei Tian ◽  
Lifang Yu ◽  
Xianglin Huang

In this article, we propose a fast and effective method for digital image contrast enhancement. The gray-level dynamic range of contrast-distorted images is extended maximally via adaptive pixel value stretching. The quantity of saturated pixels is set intelligently according to the perceptual brightness of global images. Adaptive gamma correction is also novelly used to recover the normal luminance in enhancing dimmed images. Different from prior methods, our proposed technique could be enforced automatically without complex manual parameter adjustment per image. Both qualitative and quantitative performance evaluation results show that, comparing with some recent influential contrast enhancement techniques, our proposed method achieves comparative or better enhancement quality at a surprisingly lower computational cost. Besides general computer applications, such merit should also be valuable in low-power scenarios, such as the imaging pipelines used in small mobile terminals and visual sensor network.


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