Intelligent Scene Monitoring Research Articles

SuperSoundcompass: a high-accuracy acoustic localization sensor using a small-aperture microphone array

Although miniaturized acoustic localization sensors have significant advantages in many fields, such as video conferencing, smart homes, intelligent scene monitoring, and robot audition, it is challenging to achieve high localization accuracy using them. In this study, a miniaturized acoustic localization sensor called SuperSoundcompass is developed. The system consists of seven identical microelectromechanical systems microphones distributed on a circular substrate with a radius of 4.5 cm. A high localization accuracy can be obtained with a limited number of acoustic sensors with compressive sensing applied. In order to verify the effectiveness of SuperSoundcompass, a series of simulations and experiments are performed under various conditions, such as low signal-to-noise ratio, coherent arrivals, and snapshot-starved data. The average root-mean-square error of SuperSoundcompass at 0 dB is 1.81∘. The results confirm its excellent performance in terms of accuracy.

Sound Localization and Separation in 3D Space Using a Single Microphone with a Metamaterial Enclosure.

Conventional approaches to sound localization and separation are based on microphone arrays in artificial systems. Inspired by the selective perception of the human auditory system, a multisource listening system which can separate simultaneous overlapping sounds and localize the sound sources in 3D space, using only a single microphone with a metamaterial enclosure is designed. The enclosure modifies the frequency response of the microphone in a direction‐dependent manner by giving each direction a characteristic signature. Thus, the information about the location and the audio content of sound sources can be experimentally reconstructed from the modulated mixed signals using a compressive sensing algorithm. Due to the low computational complexity of the proposed reconstruction algorithm, the designed system can also be applied in source identification and tracking. The effectiveness of the system in multiple real‐life scenarios is evaluated through multiple random listening tests. The proposed metamaterial‐based single‐sensor listening system opens a new way of sound localization and separation, which can be applied to intelligent scene monitoring and robot audition.

Security applications of computer vision

In an age which bears witness to a proliferation of Closed Circuit Television (CCTV) cameras for security and surveillance monitoring, the use of image processing and computer vision techniques which were provided as top end bespoke solutions can now be realised using desktop PC processing. Commercial Video Motion Detection (VMD) and Intelligent Scene Monitoring (ISM) systems are becoming increasingly sophisticated, aided, in no small way, by a technology transfer from previously exclusively military research sectors. Image processing is traditionally concerned with pre-processing operations such as Fourier filtering, edge detection and morphological operations. Computer vision extends the image processing paradigm to include understanding of scene content, tracking and object classification. Examples of computer vision applications include Automatic Number Plate Recognition (ANPR), people and vehicle tracking, crowd analysis and model based vision. Often image processing and computer vision techniques are developed with highly specific applications in mind and the goal of a more global understanding computer vision system remains, at least for now, outside the bounds of present technology. This paper will review some of the most recent developments in computer vision and image processing for challenging outdoor perimeter security applications. It also describes the efforts of development teams to integrate some of these advanced ideas into coherent prototype development systems.

AMETHYST: automatic alarm assessment becoming a reality

The aim of the AMETHYST (AutoMatic Event auTHentication SYSTems) project is to encourage the development of a high performance perimeter detection system which combines Video Motion Detection (VMD) technology with another type of Perimeter Intrusion Detection System (PIDS). AMETHYST will automatically assess the cause of PIDS alarms and pass to an operator those alarms likely to be caused by an intruder. It will filter out alarms not likely to have a human cause. A previous paper explaining and exploring the AMETHYST concept was presented at the 1995 Carnahan Conference. Since then PSDB has produced a single channel AMETHYST demonstrator and placed a contract for the development of an eight channel prototype AMETHYST system. This updated paper gives details of the hardware and software used with these two systems. Also described is PSDB's approach to the development of AMETHYST's automatic assessment algorithms. These will combine current expertise from Video Motion Detection (VMD) and Intelligent Scene Monitoring (ISM) systems with the unique AMETHYST approach. AMETHYST analyses picture sequences from before and after an alarm instead of continuously analysing live video. Sequences are provided by a Loop Framestore, either connected to or part of the AMETHYST system. The algorithms will be assessed and developed using PSDB's growing collection of over 150 alarm sequences.