Amelia Wong Azman

Face detection system design for real time high resolution smart camera

Recognizing faces in a crowd in real-time is a key feature which would significantly enhance Intelligent Surveillance Systems. Using a smart camera as a tool to extract faces for recognition would greatly reduce the computational load on the main processing unit. Main processing unit would not be overloaded by the demands of the high data rates of the video and could be designed solely for face recognition. The challenge is with the increasing speed and resolution of the camera sensors, a fast and robust face detection system is required for real time operation. In this paper we report on a multiple-stage face detection system that is designed for implementation on an FPGA based high resolution smart camera system. The system consist of filter stages to greatly reduce the region of interest in video image, followed by a face detection stage to accurately locate the faces. For filter stage, the algorithm is designed to be very fast so that it can be processed in real time. Meanwhile, for face detection stage, a hardware and software co-design technique is utilised to accelerate it.

An Automated Face Recognition System for Intelligence Surveillance: Smart Camera Recognizing Faces in the Crowd

Smart cameras are rapidly finding their way into intelligent surveillance systems. Recognizing faces in the crowd in real-time is one of the key features that will significantly enhance intelligent surveillance systems. The main challenge is the fact that the high volumes of data generated by high-resolution sensors make it computationally impossible for mainstream computers to process. In our proposed technique, the smart camera extracts all the faces from the full-resolution frame and sends the pixel information from these face areas to the main processing unit as a auxiliary video stream - potentially achieving massive data rate reduction. Face recognition software running on the main processing unit then performs the required pattern recognition.

Real-Time Face Detection and Tracking for High Resolution Smart Camera System

Smart Cameras are becoming more popular in Intelligent Surveillance Systems area. Recognizing faces in a crowd in real-time is a key features which would significantly enhance Intelligent Surveillance Systems. Using a high resolution smart camera as a tool to extract faces that are suitable for face recognition would greatly reduce the computational load on the main processing unit. This processing unit would not be overloaded by the demands of the high data rates required for high resolution video and could be designed solely for face recognition. In this paper we report on a multiple-stage face detection and tracking system that is designed for implementation on the NICTA high resolution (5 MP) smart camera.

Parametric analysis for designing low voltage and low frequency energy harvester booster

This work presents an ultra-low voltage DC-DC boost converter vibration-based energy harvesting. A switching gate controlled concept is used which is well suited for low vibration-based frequency and voltage applications. The 0.1-0.5 V input voltage range is linearly increased with the increase of output voltage range, 4-22 V. The transient analysis is simulated to verify the optimum value of the inductive resistance, switching rise and fall times circuit under test. The 10 kΩ load circuit is using 160 μH inductor and 10 μF load capacitor. This voltage converter is suitable for energy harvesting applications in automotive, buried electronic devices for broadband frequency range from 1 kHz to 10 kHz.

Optimizing Resources of an FPGA-based Smart Camera Architecture

The acceptance of reconfigurable platforms specifically FPGAs in embedded system design is becoming more apparent. While there are varieties of platforms available for smart camera implementation, our interest is mainly on reconfigurable platforms, specifically FPGAs. In this paper we discuss the research opportunity and the importance of hardware/software partitioning on FPGA-based smart camera platform. An overview of our current research work on the above mentioned problem is describe in this paper.

Low voltage DC power supply with spike-blocking features

RFID tags, sensors embedded with buried devices and biomedical implants all operate at low voltage levels due to power limitations. The ever increasing use these embedded devices has also created a demand in the industry for low-voltage power supplies. Since many of these circuits are mobile in nature and so are bound to operate in many different environments, the power supply must also be capable of ensuring a stable voltage output even under adverse conditions. This paper analyzes and simulates a power supply circuit that promises a low ripple factor with an element of spike-blocking capability. It centers on a phase-modulation technique that effectively cancels out 99.6% of ripples when operating with a 100 mV ac input at a frequency of 10 kHz. This active noise-cancellation technique allows for a more stable voltage output. It also has a limited inbuilt capability to block spikes. A 100 mV injected spike is brought down to only 6 mV without the use of other damping circuits. This work is therefore capable of damping a large part of the variations in the input voltage, even at low voltages.

Capacitance sensing and energy harvesting for wireless health monitoring system

In this work, a self-generated power capacitance measurement circuit for wireless health monitoring system is proposed. Hybrid energy from thermal and solar energy is expected to be used to supply the energy harvester. The present results has shown using low cost, off-the-shelf components, the capacitance measurement circuit is able to sense a linear capacitance range of 9.8 - 10.35 pF over 1.478 - 1.57 V output voltage range. This circuit also has low power consumption of 3.1 mW at frequency 40 kHz. This circuit is suitable for wireless health monitoring system.

Bioimpedance spectroscopy system for characterization of cancer cells

This paper presents a design for a Bioimpedance spectroscopy system on an FPGA board for characterization of cancer cells. The proposed hardware uses a digital auto balance bridge implemented in Verilog. Using an FPGA allows the system to be designed to have a multichannel signal acquisition from two or more sources, and to be smaller than commercial devices. The simulation results show that the system is able to detect the phase and amplitude for the impedance. The design would provide a portable bioimpedance spectroscopy system, which will be able to perform calculations and show results without the need for external hardware.

Single supply differential capacitive sensor with energy harvester compatibility

This paper presents a single supply differential capacitive sensing technique suitable to be used with a hybrid energy harvester in providing power to the circuit. The proposed differential capacitive circuit is designed based on the available off-the-shelf components. Theoretical and experimental study has been carried out to observe the performance of the circuit for various excitation frequencies. Tests that were carried out include using excitation frequencies ranging with a 0.1 pF capacitance change. Results from 40 kHz up to 400 kHz show a high level of linearity up to a 0.999 R-squared value. Range of capacitance detection can be increased by controlling the feedback capacitor, Cf, and the filter components, Rd and Cd. The sensitivity range is from 0.004 to 0.122 mV per every fF change, with ± 5 % error. The circuit consumes 3.83 mW, with a 3.3 V supply voltage. This circuit is also suitable for a wireless sensing node application.

Parametric analysis of single boost converter for energy harvester

This paper presents a conventional DC-DC boost converter for low and wide voltage supply range, suitable for energy harvesting purpose. The output voltage can be increased by controlling the transistor switching frequency, duty cycle, inductance, load capacitor, rise, and fall time. Both computer simulation and experiment results are performed in details. Experiment results have shown an error less than 6 % with the simulation. A linear trend of output voltage in the range of 4 V to 49 V is successfully converted from 100 mV to 1.5 V input voltage using low switching frequency of 2 kHz. The circuit parameter for this voltage range are L = 100 μH, D = 50 %, tr = tf = 2.9 μs considering CL = 10 μF, and RL = 10 kΩ. This circuit is suitable for medium voltage range application such as in automotive, aircraft, industry, and wireless measurement system.