Adaptive Fusion Of Particle Filtering And Spatio-Temporal Motion Energy For Human Tracking

Object tracking is an active research area nowadays due to its importance in human computer interface, teleconferencing and video surveillance. However, reliable tracking of objects in the presence of occlusions, pose and illumination changes is still a challenging topic. In this paper, we introduce a novel tracking approach that fuses two cues namely colour and spatio-temporal motion energy within a particle filter based framework. We conduct a measure of coherent motion over two image frames, which reveals the spatio-temporal dynamics of the target. At the same time, the importance of both colour and motion energy cues is determined in the stage of reliability evaluation. This determination helps maintain the performance of the tracking system against abrupt appearance changes. Experimental results demonstrate that the proposed method outperforms the other state of the art techniques in the used test datasets.

Target Detection and Tracking With Heterogeneous Sensors

We present a multimodal detection and tracking algorithm for sensors composed of a camera mounted between two microphones. Target localization is performed on color-based change detection in the video modality and on time difference of arrival (TDOA) estimation between the two microphones in the audio modality. The TDOA is computed by multiband generalized cross correlation (GCC) analysis. The estimated directions of arrival are then postprocessed using a Riccati Kalman filter. The visual and audio estimates are finally integrated, at the likelihood level, into a particle filter (PF) that uses a zero-order motion model, and a weighted probabilistic data association (WPDA) scheme. We demonstrate that the Kalman filtering (KF) improves the accuracy of the audio source localization and that the WPDA helps to enhance the tracking performance of sensor fusion in reverberant scenarios. The combination of multiband GCC, KF, and WPDA within the particle filtering framework improves the performance of the algorithm in noisy scenarios. We also show how the proposed audiovisual tracker summarizes the observed scene by generating metadata that can be transmitted to other network nodes instead of transmitting the raw images and can be used for very low bit rate communication. Moreover, the generated metadata can also be used to detect and monitor events of interest.

Mean field approach for tracking similar objects

In this paper, we consider the problem of tracking similar objects. We show how a mean field approach can be used to deal with interacting targets and we compare it with Markov Chain Monte Carlo (MCMC). Two mean field implementations are presented. The first one is more general and uses particle filtering. We discuss some simplifications of the base algorithm that reduce the computation time. The second one is based on suitable Gaussian approximations of probability densities that lead to a set of self-consistent equations for the means and covariances. These equations give the Kalman solution if there is no interaction. Experiments have been performed on two kinds of sequences. The first kind is composed of a single long sequence of twenty roaming ants and was previously analysed using MCMC. In this case, our mean field algorithms obtain substantially better results. The second kind corresponds to selected sequences of a football match in which the interaction avoids tracker coalescence in situations where independent trackers fail.

Particle Image Velocimetry Investigation of a finite amplitude pressure wave

Particle image velocimetry is used to study the motion of gas within a duct subject to the passage of a finite amplitude pressure wave. The wave is representative of the pressure waves found in the exhaust systems of internal combustion engines. Gas particles are accelerated from stationary to 150 m/s and then back to stationary in 8 ms. It is demonstrated that gas particles at the head of the wave travel at the same velocity across the duct cross section at a given point in time. Towards the tail of the wave viscous effects are plainly evident causing the flow profile to tend towards parabolic. However, the instantaneous mean particle velocity across the section is shown to match well with the velocity calculated from a corresponding measured pressure history using 1D gas dynamic theory. The measured pressure history at a point in the duct was acquired using a high speed pressure transducer of the type typically used for engine research in intake and exhaust systems. It is demonstrated that these are unable to follow the rapid changes in pressure accurately and that they are prone to resonate under certain circumstances.

Unexpected higher-order effects in charged particle impact ionization at high energies

Most of the experimental and theoretical studies of electron-impact ionization of atoms, referred to as (e, 2e), have concentrated on the scattering plane. The assumption has been that all the important physical effects will be observable in the scattering plane. However, very recently it has been shown that, for C6+-helium ionization, experiment and theory are in nice agreement in the scattering plane and in very bad agreement out of the scattering plane. This lack of agreement between experiment and theory has been explained in terms of higher-order scattering effects between the projectile and target ion. We have examined electron-impact ionization of magnesium and have observed similar higher-order effects. The results of the electron-impact ionization of magnesium indicate the possible deficiencies in the calculation of fully differential cross sections in previous heavy particle ionization work.