Object tracking using SIFT features and mean shift

A scale invariant feature transform (SIFT) based mean shift algorithm is presented for object tracking in real scenarios. SIFT features are used to correspond the region of interests across frames. Meanwhile, mean shift is applied to conduct similarity search via color histograms. The probability distributions from these two measurements are evaluated in an expectation–maximization scheme so as to achieve maximum likelihood estimation of similar regions. This mutual support mechanism can lead to consistent tracking performance if one of the two measurements becomes unstable. Experimental work demonstrates that the proposed mean shift/SIFT strategy improves the tracking performance of the classical mean shift and SIFT tracking algorithms in complicated real scenarios.

Modelling 3D camera movement for vibration characterisation and multiple object identification with application to lighting assessment

Utilising cameras as a means to survey the surrounding environment is becoming increasingly popular in a number of different research areas and applications. Central to using camera sensors as input to a vision system, is the need to be able to manipulate and process the information captured in these images. One such application, is the use of cameras to monitor the quality of airport landing lighting at aerodromes where a camera is placed inside an aircraft and used to record images of the lighting pattern during the landing phase of a flight. The images are processed to determine a performance metric. This requires the development of custom software for the localisation and identification of luminaires within the image data. However, because of the necessity to keep airport operations functioning as efficiently as possible, it is difficult to collect enough image data to develop, test and validate any developed software. In this paper, we present a technique to model a virtual landing lighting pattern. A mathematical model is postulated which represents the glide path of the aircraft including random deviations from the expected path. A morphological method has been developed to localise and track the luminaires under different operating conditions. © 2011 IEEE.

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.

The effects of TMS over dorsolateral prefrontal cortex on trans-saccadic memory of multiple objects

Humans typically make several rapid eye movements (saccades) per second. It is thought that visual working memory can retain and spatially integrate three to four objects or features across each saccade but little is known about this neural mechanism. Previously we showed that transcranial magnetic stimulation (TMS) to the posterior parietal cortex and frontal eye fields degrade trans-saccadic memory of multiple object features (Prime, Vesia, & Crawford, 2008, Journal of Neuroscience, 28(27), 6938-6949; Prime, Vesia, & Crawford, 2010, Cerebral Cortex, 20(4), 759-772.). Here, we used a similar protocol to investigate whether dorsolateral prefrontal cortex (DLPFC), an area involved in spatial working memory, is also involved in trans-saccadic memory. Subjects were required to report changes in stimulus orientation with (saccade task) or without (fixation task) an eye movement in the intervening memory interval. We applied single-pulse TMS to left and right DLPFC during the memory delay, timed at three intervals to arrive approximately 100ms before, 100ms after, or at saccade onset. In the fixation task, left DLPFC TMS produced inconsistent results, whereas right DLPFC TMS disrupted performance at all three intervals (significantly for presaccadic TMS). In contrast, in the saccade task, TMS consistently facilitated performance (significantly for left DLPFC/perisaccadic TMS and right DLPFC/postsaccadic TMS) suggesting a dis-inhibition of trans-saccadic processing. These results are consistent with a neural circuit of trans-saccadic memory that overlaps and interacts with, but is partially separate from the circuit for visual working memory during sustained fixation.

An integrated multi-sensor data fusion algorithm and autopilot iImplementation in an uninhabited surface craft

Unmanned surface vehicles (USVs) are able to accomplish difficult and challenging tasks both in civilian and defence sectors without endangering human lives. Their ability to work round the clock makes them well-suited for matters that demand immediate attention. These issues include but not limited to mines countermeasures, measuring the extent of an oil spill and locating the source of a chemical discharge. A number of USV programmes have emerged in the last decade for a variety of aforementioned purposes. Springer USV is one such research project highlighted in this paper. The intention herein is to report results emanating from data acquired from experiments on the Springer vessel whilst testing its advanced navigation, guidance and control (NGC) subsystems. The algorithms developed for these systems are based on soft-computing methodologies. A novel form of data fusion navigation algorithm has been developed and integrated with a modified optimal controller. Experimental results are presented and analysed for various scenarios including single and multiple waypoints tracking and fixed and time-varying reference bearings. It is demonstrated that the proposed NGC system provides promising results despite the presence of modelling uncertainty and external disturbances.

Multiple model bootstrap filter for maneuvering target tracking

The extension of the bootstrap filter to the multiple model target tracking problem is considered. Bayesian bootstrap filtering is a very powerful technique since it represents samples by random samples and is therefore not restricted to linear, Gaussian systems, making it ideal for the multiple model problem where very complex densities fan be generated.

Rao-Blackwellised particle filter for colour-based tracking

Colour-based particle filters have been used exhaustively in the literature given rise to multiple applications However tracking coloured objects through time has an important drawback since the way in which the camera perceives the colour of the object can change Simple updates are often used to address this problem which imply a risk of distorting the model and losing the target In this paper a joint image characteristic-space tracking is proposed which updates the model simultaneously to the object location In order to avoid the curse of dimensionality a Rao-Blackwellised particle filter has been used Using this technique the hypotheses are evaluated depending on the difference between the model and the current target appearance during the updating stage Convincing results have been obtained in sequences under both sudden and gradual illumination condition changes Crown Copyright (C) 2010 Published by Elsevier B V All rights reserved

Optical observations of 23 distant Jupiter Family Comets, including 36P/Whipple at multiple phase angles

We present photometry on 23 Jupiter Family Comets (JFCs) observed at large heliocentric distance, primarily using the 2.5-m Isaac Newton Telescope (INT). Snapshot images were taken of 17 comets, of which five were not detected, three were active and nine were unresolved and apparently inactive. These include 103P/Hartley 2, the target of the NASA Deep Impact extended mission, EPOXI. For six comets we obtained time-series photometry and use this to constrain the shape and rotation period of these nuclei. The data are not of sufficient quantity or quality to measure precise rotation periods, but the time-series do allow us to measure accurate effective radii and surface colours. Of the comets observed over an extended period, 40P/Väisälä 1, 47P/Ashbrook-Jackson and P/2004 H2 (Larsen) showed faint activity which limited the study of the nucleus. Light curves for 94P/Russell 4 and 121P/Shoemaker-Holt 2 reveal rotation periods of around 33 and 10h, respectively, although in both cases these are not unique solutions. 94P was observed to have a large range in magnitudes implying that it is one of the most elongated nuclei known, with an axial ratio a/b >= 3. 36P/Whipple was observed at five different epochs, with the INT and ESO's 3.6-m NTT, primarily in an attempt to confirm the preliminary short rotation period apparent in the first data set. The combined data set shows that the rotation period is actually longer than 24h. A measurement of the phase function of 36P's nucleus gives a relatively steep ß = 0.060 +/- 0.019. Finally, we discuss the distribution of surface colours observed in JFC nuclei, and show that it is possible to trace the evolution of colours from the Kuiper Belt Object (KBO) population to the JFC population by applying a `dereddening' function to the KBO colour distribution.