Towards commoditized smart-camera design

2013 ◽  
Vol 59 (10) ◽  
pp. 847-858 ◽  
Author(s):  
Boštjan Murovec ◽  
Janez Perš ◽  
Rok Mandeljc ◽  
Vildana Sulić Kenk ◽  
Stanislav Kovačič
Keyword(s):  
Smart Camera ◽  
Camera Design

Smart camera design for intensive embedded computing

2005 ◽  
Vol 11 (4) ◽  
pp. 282-289 ◽  
Author(s):  
Barthélémy Heyrman ◽  
Michel Paindavoine ◽  
Renaud Schmit ◽  
Laurent Letellier ◽  
Thierry Collette
Keyword(s):  
Smart Camera ◽  
Embedded Computing ◽  
Camera Design

scholarly journals Smart Video Surveillance System Based on Edge Computing

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2958
Author(s):  
Antonio Carlos Cob-Parro ◽  
Cristina Losada-Gutiérrez ◽  
Marta Marrón-Romera ◽  
Alfredo Gardel-Vicente ◽  
Ignacio Bravo-Muñoz
Keyword(s):  
Computer Vision ◽  
Video Surveillance ◽  
Surveillance System ◽  
Video Surveillance System ◽  
Smart Camera ◽  
People Detection ◽  
Camera System ◽  
Edge Node ◽  
New Processing ◽  
Processor Unit

New processing methods based on artificial intelligence (AI) and deep learning are replacing traditional computer vision algorithms. The more advanced systems can process huge amounts of data in large computing facilities. In contrast, this paper presents a smart video surveillance system executing AI algorithms in low power consumption embedded devices. The computer vision algorithm, typical for surveillance applications, aims to detect, count and track people’s movements in the area. This application requires a distributed smart camera system. The proposed AI application allows detecting people in the surveillance area using a MobileNet-SSD architecture. In addition, using a robust Kalman filter bank, the algorithm can keep track of people in the video also providing people counting information. The detection results are excellent considering the constraints imposed on the process. The selected architecture for the edge node is based on a UpSquared2 device that includes a vision processor unit (VPU) capable of accelerating the AI CNN inference. The results section provides information about the image processing time when multiple video cameras are connected to the same edge node, people detection precision and recall curves, and the energy consumption of the system. The discussion of results shows the usefulness of deploying this smart camera node throughout a distributed surveillance system.

Low-cost Smart Camera System for Water Stress Detection in Crops

2020 ◽  
Author(s):  
Paula Ramos-Giraldo ◽  
S. Chris Reberg-Horton ◽  
Steven Mirsky ◽  
Edgar Lobaton ◽  
Anna M. Locke ◽  
...  
Keyword(s):  
Water Stress ◽  
Low Cost ◽  
Smart Camera ◽  
Stress Detection ◽  
Camera System

FPGA Based Embedded Implementation of Video Summary Generation Scheme in Smart Camera

2011 ◽  
Vol 403-408 ◽  
pp. 516-521 ◽  
Author(s):  
Sanjay Singh ◽  
Srinivasa Murali Dunga ◽  
AS Mandal ◽  
Chandra Shekhar ◽  
Santanu Chaudhury
Keyword(s):  
Detection Algorithm ◽  
Smart Camera ◽  
Camera System ◽  
Smart Cameras ◽  
Embedded Platform ◽  
Video Summary ◽  
Embedded Design ◽  
Multiple Frames ◽  
Computationally Intensive ◽  
Embedded Implementation

In any remote surveillance scenario, smart cameras have to take intelligent decisions to generate summary frames to minimize communication and processing overhead. Video summary generation, in the context of smart camera, is the process of merging the information from multiple frames. A summary generation scheme based on clustering based change detection algorithm has been implemented in our smart camera system for generating frames to deliver requisite information. In this paper we propose an embedded platform based framework for implementing summary generation scheme using HW-SW Co-Design based methodology. The complete system is implemented on Xilinx XUP Virtex-II Pro FPGA board. The overall algorithm is running on PowerPC405 and some of the blocks which are computationally intensive and more frequently called are implemented in hardware using VHDL. The system is designed using Xilinx Embedded Design Kit (EDK).

Toward low latency gesture control using smart camera network

2008 ◽  
Author(s):  
Zoran Zivkovic ◽  
Vitaly Kliger ◽  
Richard Kleihorst ◽  
Alexander Danilin ◽  
Ben Schueler ◽  
...  
Keyword(s):  
Low Latency ◽  
Smart Camera ◽  
Camera Network ◽  
Gesture Control
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