An adaptive motion model for person tracking with instantaneous head-pose features

This letter presents novel behaviour-based tracking of people in low-resolution using instantaneous priors mediated by head-pose. We extend the Kalman Filter to adaptively combine motion information with an instantaneous prior belief about where the person will go based on where they are currently looking. We apply this new method to pedestrian surveillance, using automatically-derived head pose estimates, although the theory is not limited to head-pose priors. We perform a statistical analysis of pedestrian gazing behaviour and demonstrate tracking performance on a set of simulated and real pedestrian observations. We show that by using instantaneous `intentional' priors our algorithm significantly outperforms a standard Kalman Filter on comprehensive test data.

Interferometer for Co-operating Target Motion Detection

A correlation interferometer working with a cooperation target operating at 2.2GHz center frequency is presented. This simplified interferometer presented here uses a
lock-in amplifier to significantly increase system sensitivity when used in conjunction with a co-operating target signaling using amplitude modulation. The system is verified by detecting the angular velocity of passing tagged target. Experimental results show detectable range up over 110 meters in a multipath environment using a 10dBm EIRP tag.

Effect of osteoporosis on bone mineral density and fracture repair in a rat femoral fracture model

Osteoporosis (OP) is one of the most prevalent bone diseases worldwide with bone fracture the major clinical consequence. The effect of OP on fracture repair is disputed and although it might be expected for fracture repair to be delayed in osteoporotic individuals, a definitive answer to this question still eludes us. The aim of this study was to clarify the effect of osteoporosis in a rodent fracture model. OP was induced in 3-month-old rats (n = 53) by ovariectomy (OVX) followed by an externally fixated, mid-diaphyseal femoral osteotomy at 6 months (OVX group). A further 40 animals underwent a fracture at 6 months (control group). Animals were sacrificed at 1, 2, 4, 6, and 8 weeks postfracture with outcome measures of histology, biomechanical strength testing, pQCT, relative BMD, and motion detection. OVX animals had significantly lower BMD, slower fracture repair (histologically), reduced stiffness in the fractured femora (8 weeks) and strength in the contralateral femora (6 and 8 weeks), increased body weight, and decreased motion. This study has demonstrated that OVX is associated with decrease in BMD (particularly in trabecular bone) and a reduction in the mechanical properties of intact bone and healing fractures. The histological, biomechanical, and radiological measures of union suggest that OVX delayed fracture healing. (C) 2007 Orthopaedic Research Society. Published by Wiley Periodicals.

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.

Detection of aberrant behaviour in home environments from video sequence

We introduce an application for the detection of aberrant behaviour within home based environments, with a focus on repetitive actions, which may be present in instance of persons suffering from dementia. Video based analysis has been used to detect the motion of a person within a given scene in addition to tracking them over the time. Detection of repetitive actions has been based on the analysis of a person's trajectory using the principles of signal correlation. Along with the ability to detect repetitive motion the developed approach also has the ability to measure the amount of activity/inactivity within the scene during a given period of time. Our results showed that the developed approach had the ability to detect all patterns in the data set examined with an average accuracy of 96.67%. This work has therefore validated the proposed concept of video based analysis for the detection of repetitive activities.

Enhancing Linear Programming with Motion Modeling for Multi-target Tracking

In this paper we extend the minimum-cost network flow approach to multi-target tracking, by incorporating a motion model, allowing the tracker to better cope with longterm occlusions and missed detections. In our new method, the tracking problem is solved iteratively: Firstly, an initial tracking solution is found without the help of motion information. Given this initial set of tracklets, the motion at each detection is estimated, and used to refine the tracking solution.
Finally, special edges are added to the tracking graph, allowing a further revised tracking solution to be found, where distant tracklets may be linked based on motion similarity. Our system has been tested on the PETS S2.L1 and Oxford town-center sequences, outperforming the baseline system, and achieving results comparable with the current state of the art.