Hamid K. Aghajan

MeshEye: a hybrid-resolution smart camera mote for applications in distributed intelligent surveillance

Surveillance is one of the promising applications to which smart camera motes forming a vision-enabled network can add increasing levels of intelligence. We see a high degree of in-node processing in combination with distributed reasoning algorithms as the key enablers for such intelligent surveillance systems. To put these systems into practice still requires a considerable amount of research ranging from mote architectures, pixel-processing algorithms, up to distributed reasoning engines. This paper introduces MeshEye, an energy-efficient smart camera mote architecture that has been designed with intelligent surveillance as the target application in mind. Special attention is given to MeshEyes unique vision system: a low-resolution stereo vision system continuously determines position, range, and size of moving objects entering its field of view. This information triggers a color camera module to acquire a high-resolution image sub-array containing the object, which can be efficiently processed in subsequent stages. It offers reduced complexity, response time, and power consumption over conventional solutions. Basic vision algorithms for object detection, acquisition, and tracking are described and illustrated on real- world data. The paper also presents a basic power model that estimates lifetime of our smart camera mote in battery-powered operation for intelligent surveillance event processing.

Handbook of Ambient Intelligence and Smart Environments

Ambient Intelligence (AmI) has recently been adopted as a term referring to a multidisciplinary subject which embraces a variety of pre-existing fields of computer science and engineering. Given the diversity of potential applications this relationship naturally extends to other areas of science, such as education, health and social care, entertainment, sports, and transportation, to name a few. AmI brings these resources and many other areas together to provide flexible and intelligent services to users acting in their environments. Handbook of Ambient Intelligence and Smart Environments is a comprehensive presentation of the latest developments in the burgeoning research area of ambient intelligence and smart environments. Written by leading international experts, this seminal reference organizes all major concepts, theories, methodologies, trends, and challenges into a coherent, unified repository. About this handbook: Offers a current and thorough review of Ambient Intelligence and examines the relative physical infrastructure of smart environments Features application-oriented coverage and presents current projects on the subject Provides coverage from leading researchers and practitioners in computer science and engineering communities Describes infastructure and how sensors are networked and utilized in application settings Explores technology that can be built over a networked sensing infrastructure to make resources widely available in an unobtrusive way Studies the interaction between humans and artifiical systems Probes developments that aim to make artificial systems more rational Addresses Multi-Agent Systemssystems that contribute to the resources of an artificial system which can be used to understand different sitautions and decide intelligently Investigates a wide range of application ans well as consideration of the impact this technology can have in daily lives. Provides insight into some of the recent major projects developed around the world. This complete volume is an exceptional tool for research scientists, practitioners, senior undergraduate and graduate students in computer science and engineering. This book also presents a useful text for professionals working in service science, education, education, health and social care, entertainment, sports, transportation and urban development.

Smart home care network using sensor fusion and distributed vision-based reasoning

A wireless sensor network employing multiple sensing and event detection modalities and distributed processing is proposed for smart home monitoring applications. Image sensing and vision-based reasoning are employed to verify and further analyze events reported by other sensors. The system has been developed to address the growing application domain in caregiving to the elderly and persons in need of monitored living, who care to live independently while enjoying the assurance of timely access to caregivers when needed. An example of sensed events is the accidental fall of the person under care. A wireless badge node acts as a bridge between the user and the network. The badge node provides user-centric event sensing functions such as detecting falls, and also provides a voice communication channel between the user and the caregiving center when the system detects an alert and dials the center. The voice connection is carried over an IEEE 802.15.4 radio link between the user badge and another node in the network that acts as a modem. Using signal strength measurements, the network nodes keep track of the approximate location of the user in the monitoring environment.The network also includes wall-mounted image sensor nodes, which are triggered upon detection of a fall to analyze their field-of-view and provide the caregiving center with further information about the user s status. A description of the developed network and several examples of the vision-based reasoning algorithm are presented in the paper.

The effect of time synchronization errors on the performance of cooperative MISO systems

We consider a wireless sensor network scenario where closely packed nodes can he grouped into clusters. Although each node might have only a single antenna, nodes within a cluster can cooperate during transmission or reception, thereby forming a cooperative multiple input multiple output (MIMO) system. Much of the work in the area of cooperative MIMO has assumed perfect synchronization between the nodes in the network and the associated benefits have been investigated. We examine this assumption in a system where a cluster of nodes cooperatively transmits to a single receive node over a flat fading channel. We evaluate the effect of clock jitter between nodes on the performance of this cooperative multiple input single output (MISO) system. The clock jitter at the transmit nodes results in the lack of a reference clock at the receive node and causes inter-symbol interference (ISI). This leads to a performance degradation in the system. However, simulation results indicate that jitters as large as 10% of the bit time do not have much effect on the BER performance of the system. We also show that when the channel is not undergoing fading, the power penalty due to the clock jitter is independent of the number of transmit nodes and the penalty increases as the SNR increases.

Ambient Intelligence and Smart Environments: A State of the Art

Advances in the miniaturization of electronics is allowing computing devices with various capabilities and interfaces to become part of our daily life. Sensors, actuators, and processing units can now be purchased at very affordable prices. This technology can be networked and used with the coordination of highly intelligent software to understand the events and relevant context of a specific environment and to take sensible decisions in real-time or a posteriori.

Distributed vision-based accident management for assisted living

We consider the problem of assisting vulnerable people and their carers to reduce the occurrence, and concomitant consequences, of accidents in the home. A wireless sensor network employing multiple sensing and event detection modalities and distributed processing is proposed for smart home monitoring applications. Distributed vision-based analysis is used to detect occupants posture, and features from multiple cameras are merged through a collaborative reasoning function to determine significant events. The ambient assistance provided will assume minimal expectations on the technology people have to directly interact with. Vision-based technology is coupled with AI-based algorithms in such a way that occupants do not have to wear sensors, other than an unobtrusive identification badge, or learn and remember to use a specific device. In addition the system can assess situations, anticipate problems, produce alerts, advise carers and provide explanations.

SLIDE: subspace-based line detection

An analogy is made between each straight line in an image and a planar propagating wavefront impinging on an array of sensors so as to obtain a mathematical model exploited in recent high resolution methods for direction-of-arrival estimation in sensor array processing. The new so-called SLIDE (subspace-based line detection) algorithm then exploits the spatial coherence between the contributions of each line in different rows of the image to enhance and distinguish a signal subspace that is defined by the desired line parameters. SLIDE yields closed-form and high resolution estimates for line parameters, and its computational complexity and storage requirements are far less than those of the standard method of the Hough transform. If unknown a priori, the number of lines is also estimated in the proposed technique. The signal representation employed in this formulation is also generalized to handle grey-scale images as well. The technique has also been generalized to fitting planes in 3-D images. Some practical issues of the proposed technique are given. >

Sensor array processing techniques for super resolution multi-line-fitting and straight edge detection

A signal processing method is developed for solving the problem of fitting multiple lines in a two-dimensional image. It formulates the multi-line-fitting problem in a special parameter estimation framework such that a signal structure similar to the sensor array processing signal representation is obtained. Then the recently developed algorithms in that formalism can be exploited to produce super-resolution estimates for line parameters. The number of lines may also be estimated in this framework. The signal representation used can be generalized to handle problems of line fitting and of straight edge detection. Details of the proposed algorithm and several experimental results are presented. The method exhibits considerable computational speed superiority over existing single- and multiple-line-fitting algorithms such as the Hough transform method. Potential applications include road tracking in robotic vision, mask wafer alignment in semiconductor manufacturing, aerial image analysis, text alignment in document analysis, and particle tracking in bubble chambers.

Automated direct patterned wafer inspection

A self-reference technique is developed for detecting the location of defects in repeated pattern wafers and masks. The application area of the proposed method includes inspection of memory chips, shift registers, switch capacitors, and CCD arrays. Using high resolution spectral estimation algorithms, the proposed technique first extracts the period and structure of repeated patterns from the image to sub-pixel resolution, and then produces a defect-free reference image for making comparison with the actual image. Since the technique acquires all its needed information from a single image, there is no need for a database image, a scaling procedure, or any a-priori knowledge about the repetition period of the patterns.<<ETX>>

Visual analysis of child-adult interactive behaviors in video sequences

Kids activity means a lot to their parents, and in the analysis of the activities, video retrieval has played an important role. In this paper, we propose an effective approach for the retrieval of the kids activities from home videos. The video sequences are taken from our test-bed environment that is designed in the form of a smart home, and feature various types of child-adult interactions. We present a novel retrieval method with two steps, first using spatio-temporal matching to obtain a coarse result, And then we propose a method to learn dominant child-adult interactive behaviors based on a sequence of home videos. Based on these dominant behaviors, we get rid of some false retrieval and obtain fine result. We implement and test our methodology on a newly-introduced dataset containing several types of kids activities, and the retrieval result shows its potential application in the video analysis demain, it can find out most of the video clips relevant to the query one.