Particle filtering framework is widely used on tracking applications. In surveillance systems, it often combines with color information to achieve visual object tracking. However, the resource usage of this framework, including memory bandwidth and operation cycles, is very intensive to make a low cost real time object tracking unattainable. In this paper, an efficient architecture of color based particle filtering tracking with dual cache is proposed. It utilizes a frame cache to reduce memory bandwidth of loading frame data, and a histogram cache to reduce operation cycles when constructing color histogram. The experimental results show that this architecture can improve the performance to real time on a high system specification.

One of the principal cues believed to be used by listeners to estimate the distance to a sound source is the ratio of energies along the direct and indirect paths to the receiver. In essence, this “direct-to-reverberant” energy ratio reveals the absolute distance component of the direct energy by normalizing by what is assumed to be distance-independent reverberant energy. Earlier approaches to direct-to-reverberant energy ratio calculation made use of the estimated room impulse response, but these techniques are computationally expensive and inaccurate in practice. This paper proposes and evaluates an alternative approach which uses binaural signals to segregate energy arriving from the estimated direction of the direct source from that arriving from other directions, employing a novel binaural equalization-cancellation technique. The system is integrated with a probabilistic inference framework, particle filtering, to handle the nonstationarity of energy-based measurements. The algorithm is capable of using reverberation to estimate source distance in large rooms with errors of less than 1 m for static sources and 1.5-3.5 m for sources with varying degrees of motion complexity. Model performance can be accounted for largely in terms of a competition between auditory horizon and source energy fluctuation effects.

This paper describes the acquisition and content of a new multi-modal database. Some tools for making use of the data streams are also presented. The Computational Audio-Visual Analysis (CAVA) database is a unique collection of three synchronised data streams obtained from a binaural microphone pair, a stereoscopic camera pair and a head tracking device. All recordings are made from the perspective of a person; i.e. what would a human with natural head movements see and hear in a given environment. The database is intended to facilitate research into humans' ability to optimise their multi-modal sensory input and fills a gap by providing data that enables human centred audio-visual scene analysis. It also enables 3D localisation using either audio, visual, or audio-visual cues. A total of 50 sessions, with varying degrees of visual and auditory complexity, were recorded. These range from seeing and hearing a single speaker moving in and out of field of view, to moving around a 'cocktail party' style situation, mingling and joining different small groups of people chatting.

A method for estimating sound source distance in dynamic auditory „scenes‟ using binaural data is presented. The technique requires little prior knowledge of the acoustic environment. It consists of feature extraction for two dynamic distance cues, motion parallax and acoustic τ, coupled with an inference framework for distance estimation. Sequential and nonsequential models are evaluated using simulated anechoic and reverberant spaces. Sequential approaches based on particle filtering more than half the distance estimation error in all conditions relative to the non-sequential models. These results confirm the value of active behaviour and probabilistic reasoning in auditorily-inspired models of distance perception.

A VLSI architecture for the MPEG-2/4 AAC encoding accelerator is proposed This hardware IP is an AMBA AHB peripheral component that can easily integrate with any other RISC based SoC platform. Preserving the flexibility of library development and achieving an area cost-efficient acceleration, the quantisation rate-loop module is targeted to be the processing function. In the design, an easy Huffman codebook search method is also developed for the viability of hardware realization. The final work has been verified in an FPGA and synthesized to a 0.18 mum standard cell library. It can speed up an audio recording application by 1.5-times and achieve a real-time encoding for stereo 44.1 kHz PCM data with additional 160 MHz ARM core