Embedded Video Surveillance Research Articles

Research on the Wireless Video Surveillance System Based on Linux

With the new development of embedded technology, image compression and wireless transmission technology, wireless video surveillance system based on embedded system has become the tendency of development in the field of video surveillance. This paper combines the character of embedded system with wireless transmission technology, researches and designs a solution of wireless video surveillance system based on Linux. The embedded video surveillance system uses C/S framework. The server based on ARM11 and Linux is designed to process video image including capture, preview, compression and transmission. The PC as a client is built to receive, decode, display and setup the video.

Embedded Video Surveillance Based Moving Object Detection and Tracking

Background reckoning and the foreground, play prominent roles in the tasks of visual detection and tracking of objects. Moving Object Detection has been widely used in sundry discipline such as intelligent systems, security systems, video monitoring systems, banking places, provisionary systems, and so on. In this paper proposes moving objects detection and tracking method based on Embedded Video Surveillance. The method is based on using lines computed by a gradient-based optical flow and an edge detector gradient-based optical flow and edges are well matched for accurate computation of velocity, not much attention is paid to creating systems for tracking objects using this feature. The proposed method is compared with a recent work, proving its superior performance and when we want to represent high quality videos and images with, lower bit rate, and also suitable for real-world live video applications. This method reduces influences of foreground objects to the background model. The simulation results show that the background image can be obtained precisely and the moving objects recognition is achieved effectively.

Low-cost multiple object tracking for embedded vision applications

This paper presents a low-cost multiple object tracking (MOT) technique by employing a novel appearance update model for object appearance modeling using K-means. The state-of-the-art work has attained a very high accuracy without considering the real-time aspects necessitated by currently trending embedded vision platforms. The major research on multiple object tracking is used to update the appearance model in every frame while discounting its persistent nature. The proposed appearance update model reduces the computational cost of the state-of-the-art MOT 6-fold by exploiting this facet of persistent appearance over the sequence of frames. To ensure accuracy, the proposed model is tested on different publicly available standard datasets with challenging situations for both indoor and outdoor scenarios. The experimental results illustrate that our model successfully achieves multiple object tracking while coping with long-term and complete occlusion. The proposed method achieves the same accuracy in comparison with the state-of-the-art baseline methods. Moreover, and most importantly, the proposed method is cost-effective in terms of computing and/or memory requirements in comparison to the state-of-the-art techniques. All these traits make our design very suitable for real-time and embedded video surveillance applications with low computing/memory resources.

Image super-resolution for heterogeneous embedded smart devices and displays in smart global village

The smart city has become the key factor of the progression of the future city, and the smart device sensors are widely used in real-time applications to achieve smart city. Especially, super-resolution techniques have resulted in embedded video surveillance turning into a principal method of protecting public security. In this paper, we present a super-resolution method for embedded system which interpolates unknown pixel components at the zero-padded signals. This work is for a smart global village by applying real-time embedded monitoring system (such as traffic purpose) using visual sensor networks. In general, images are obtained from a number of visual sensor nodes and cameras. The visual sensor node conveys them to the computer devices for processing. To this end, a process called image super-resolution is needed. In this work, a filter design method is researched by using a regression approach. There are two main stages of this work. First, we study filter designing method training dataset. Second, we implement super-resolution process by applying pre-designed filters. Experimental results are given to show the superiority of the proposed method compared to the conventional methods. This paper also demonstrates super-resolution results obtained by designed filter and its implementation.

K‐means based multiple objects tracking with long‐term occlusion handling

This study presents a novel multiple objects tracking (MOT) approach that models object's appearance based on K‐means, while introducing a new statistical measure for association of objects after occlusion. The proposed method is tested on several standard datasets dealing complex situations in both indoor and outdoor environments. The experimental results show that the proposed model successfully tracks multiple objects in the presence of occlusion with high accuracy. Moreover, the presented work has the capability to deal long term and complete occlusion without any prior training of the shape and motion model of the objects. Accuracy of the proposed method is comparable with that of the existing state‐of‐the‐art techniques as it successfully deals with all MOT cases in the standard datasets. Most importantly, the proposed method is cost effective in terms of memory and/or computation as compared with that of the existing state‐of‐the‐art techniques. These traits make the proposed system very useful for real‐time embedded video surveillance platforms especially those that have low memory/compute resources.

The Research on Fire Fighting System of Industrial and Civil Buildings Based on Network Video

With the rapid development of the electronic technology, multimedia technology and network technology, video surveillance system is going to the embedded, digital, networked direction. Taking full advantage of LSI and networks of scientific and technological achievements, the embedded video surveillance system achieves delicate volume, stable performance, facilitates the communication of the surveillance equipment.The project is in arm microprocessor platform, and porting embedded linux system in it. It completes video capturing, compression, transmission and control tasks. The hard devices select the ARM9 (S3C2410) as the main processor in the system; and the USB camera as the device of video capture. In order to reduce the cost of the product, Based on the architecture and with the open source software in linux, the whole embedded video surveillance system is implemented.

Design and Implementation of Embedded Video Surveillance System Based on Human Detection

In order to get information timely when elderly people fall down and need assistance, a kind of intelligent video surveillance system is designed and implemented. By using this system, the elderly dont need to wear any device. The H.264 video standard, the embedded technology, network technology, video surveillance technology and image processing technology are mixed used to detect human gesture in the video stream monitored. This system updates the background by the Gauss mixture model. The moving target is segmented by using the background subtraction algorithm. Experiments show that the system can be remote monitoring and detecting attitude. When the people falls down the system can automatically alarm, and satisfy the requirement of the timeliness, accuracy and stability.

Context modeling combined with motion analysis for moving ship detection in port surveillance

In port surveillance, video-based monitoring is a valuable supplement to a radar system by helping to detect smaller ships in the shadow of a larger ship and with the possibility to detect nonmetal ships. Therefore, automatic video-based ship detection is an important research area for security control in port regions. An approach that automatically detects moving ships in port surveillance videos with robustness for occlusions is presented. In our approach, important elements from the visual, spatial, and temporal features of the scene are used to create a model of the contextual information and perform a motion saliency analysis. We model the context of the scene by first segmenting the video frame and contextually labeling the segments, such as water, vegetation, etc. Then, based on the assumption that each object has its own motion, labeled segments are merged into individual semantic regions even when occlusions occur. The context is finally modeled to help locating the candidate ships by exploring semantic relations between ships and context, spatial adjacency and size constraints of different regions. Additionally, we assume that the ship moves with a significant speed compared to its surroundings. As a result, ships are detected by checking motion saliency for candidate ships according to the predefined criteria. We compare this approach with the conventional technique for object classification based on support vector machine. Experiments are carried out with real-life surveillance videos, where the obtained results outperform two recent algorithms and show the accuracy and robustness of the proposed ship detection approach. The inherent simplicity of our algorithmic subsystems enables real-time operation of our proposal in embedded video surveillance, such as port surveillance systems based on moving, nonstatic cameras.

Research of Multimedia Data Transmission Based on UDP

The article focuses on the research of a reliable data transmission extension protocol -- UDT based on UDP, the related implementation method and transmission control method of multimedia data real-time and reliable transmission, the improvement to algorithm of its related methods in specific applications; as well as the improvement to AIMD (Additive Increase and Multiplicative Decrease) congestion controlling algorithm, proposing DAIMD congestion controlling algorithm; the sending rate increment is changed from the constant quantity to the variable quantity which continuously reduces with the continuous increase of the sending rates, so it not only makes a more rational use of limited network bandwidth, also reduces the larger oscillation in the network data transmission; the improvement of validation mechanisms, propose validation mechanisms based on the combination of time and data packets numbers, and improve the efficiency of data transmission. When the multimedia data network transmits, the transmitter and receiver need to identify a network transmission protocol. According to the above analysis, UDP is a simple transmission level protocol, non-connection-oriented, and itself does not provide data retransmission and confirmation, therefore adopting UDP as the network transmission protocol can improve the data transmission efficiency, besides UDP supports the webcast function, suitable for multimedia data network transmission [1]. However, the characteristic of multimedia data network transmission requests the network transmission protocol can handle the phenomenon of delay and vibration in the transmission process; can handle bursting multimedia data transmission; can judge the network condition according to the reception quality of the receiver and the sender can make the appropriate response; can ensure the reliability of multimedia data network transmission and so on. Features of UDP its own design make it deal with such situations not very well, also UDP limits the sending data packet size each time; when the multimedia data network transmits, a video data often exceed this limit. Therefore, according to the previous analysis of multimedia data network transmission characteristics and technical requirements, this article studies the reliable data transmission extension protocol -- UDT based on UDP, and improves the related algorithm and control mechanism in the protocol to make it more suitable for the multimedia data network transmission in the embedded video surveillance system.

Customizing Multiprocessor Implementation of an Automated Video Surveillance System

This paper reports on the development of an automated embedded video surveillance system using two customized embedded RISC processors. The application is partitioned into object tracking and video stream encoding subsystems. The real-time object tracker is able to detect and track moving objects by video images of scenes taken by stationary cameras. It is based on the block-matching algorithm. The video stream encoding involves the optimization of an international telecommunications union (ITU)-T H.263 baseline video encoder for quarter common intermediate format (QCIF) and common intermediate format (CIF) resolution images. The two subsystems running on two processor cores were integrated and a simple protocol was added to realize the automated video surveillance system. The experimental results show that the system is capable of detecting, tracking, and encoding QCIF and CIF resolution images with object movements in them in real-time. With low cycle-count, low-transistor count, and low-power consumption requirements, the system is ideal for deployment in remote locations.

Customizing Multiprocessor Implementation of an Automated Video Surveillance System

This paper reports on the development of an automated embedded video surveillance system using two customized embedded RISC processors. The application is partitioned into object tracking and video...