DC-image for real time compressed video matching

This chapter presents a suggested framework for video matching based on local features extracted from the DC-image of MPEG compressed videos, without full decompression. In addition, the relevant arguments and supporting evidences are discussed. Several local feature detectors will be examined to select the best for matching using the DC-image. Two experiments are carried to support the above. The first is comparing between the DC-image and I-frame, in terms of matching performance and computation complexity. The second experiment compares between using local features and global features regarding compressed video matching with respect to the DC-image. The results confirmed that the use of DC-image, despite its highly reduced size, it is promising as it produces higher matching precision, compared to the full I-frame. Also, SIFT, as a local feature, outperforms most of the standard global features. On the other hand, its computation complexity is relatively higher, but it is still within the real-time margin which leaves a space for further optimizations that can be done to improve this computation complexity

Transparent support for partial rollback in software transactional memories

The Software Transactional Memory (STM) paradigm has gained momentum thanks to its ability to provide synchronization transparency in concurrent applications. With this paradigm, accesses to data structures that are shared among multiple threads are carried out within transactions, which are properly handled by the STM layer with no intervention by the application code. In this article we propose an enhancement of typical STM architectures which allows supporting partial rollback of active transactions, as opposed to the typical case where a rollback of a transaction entails squashing all the already-performed work. Our partial rollback scheme is still transparent to the application programmer and has been implemented for x86-64 architectures and for the ELF format, thus being largely usable on POSIX-compliant systems hosted on top of off-the-shelf architectures. We integrated it within the TinySTM open-source library and we present experimental results for the STAMP STM benchmark run on top of a 32-core HP ProLiant server. © 2013 Springer-Verlag

Traffic monitoring using image processing : a thesis presented in partial fulfillment of the requirements for the degree of Master of Engineering in Information and Telecommunications Engineering at Massey University, Palmerston North, New Zealand

Traffic monitoring involves the collection of data describing the characteristics of vehicles and their movements. Such data may be used for automatic tolls, congestion and incident detection, law enforcement, and road capacity planning etc. With the recent advances in Computer Vision technology, videos can be analysed automatically and relevant information can be extracted for particular applications. Automatic surveillance using video cameras with image processing technique is becoming a powerful and useful technology for traffic monitoring. In this research project, a video image processing system that has the potential to be developed for real-time application is developed for traffic monitoring including vehicle tracking, counting, and classification. A heuristic approach is applied in developing this system. The system is divided into several parts, and several different functional components have been built and tested using some traffic video sequences. Evaluations are carried out to show that this system is robust and can be developed towards real-time applications

Thermo-visual feature fusion for object tracking using multiple spatiogram trackers

In this paper, we propose a framework that can efficiently combine features for robust tracking based on fusing the outputs of multiple spatiogram trackers. This is achieved without the exponential increase in storage and processing that other multimodal tracking approaches suffer from. The framework allows the features to be split arbitrarily between the trackers, as well as providing the flexibility to add, remove or dynamically weight features. We derive a mean-shift type algorithm for the framework that allows efficient object tracking with very low computational overhead. We especially target the fusion of thermal infrared and visible spectrum features as the most useful features for automated surveillance applications. Results are shown on multimodal video sequences clearly illustrating the benefits of combining multiple features using our framework

Deep-tissue focal fluorescence imaging with digitally time-reversed ultrasound-encoded light.

Fluorescence imaging is one of the most important research tools in biomedical sciences. However, scattering of light severely impedes imaging of thick biological samples beyond the ballistic regime. Here we directly show focusing and high-resolution fluorescence imaging deep inside biological tissues by digitally time-reversing ultrasound-tagged light with high optical gain (~5×10(5)). We confirm the presence of a time-reversed optical focus along with a diffuse background-a corollary of partial phase conjugation-and develop an approach for dynamic background cancellation. To illustrate the potential of our method, we image complex fluorescent objects and tumour microtissues at an unprecedented depth of 2.5 mm in biological tissues at a lateral resolution of 36 μm×52 μm and an axial resolution of 657 μm. Our results set the stage for a range of deep-tissue imaging applications in biomedical research and medical diagnostics

Direct imaging with highly diluted apertures. I. Field of view limitations

Future optical interferometric instrumentation mainly relies on the availability of an efficient cophasing system: once available, what has so far postponed the relevance of direct imaging with an interferometer will vanish. This paper focuses on the actual limits of snapshot imaging, inherent to the use of a sparse aperture: the number of telescopes and the geometry of the array impose the maximum extent of the field of view and the complexity of the sources. A second limitation may arise from the beam combination scheme. Comparing already available solutions, we show that the so called hypertelescope mode (or densified pupil) is ideal. By adjusting the direct imaging field of view to the useful field of view offered by the array, the hypertelescope makes an optimal use of the collected photons. It optimizes signal to noise ratio, drastically improves the luminosity of images and makes the interferometer compatible with coronagraphy, without inducing any loss of useful field of view.Comment: 13 pages, 6 figures, accepted for publication in MNRAS. Full-resolution version available at http://www.obs-hp.fr/~lardiere/publi/2006-Lardiere-MNRAS.pd