Measurements of vibrations, such as sound hitting an object or running a motor, are widely used in industry and research. Traditional methods need either direct contact with the object or a laser vibrometer. Although computer vision methods have been applied to solve this problem, high speed cameras are usually preferred. This study employs a consumer level rolling shutter camera for extracting main frequency components of small vibrations. A rolling shutter camera exposes continuously over time on the vertical direction of the sensor, and produces images with shifted rows of objects. We utilize the rolling shutter effect to boost our capability to extract vibration frequencies higher than the frame rate. Assuming the vibration amplitude of the target results in a horizontal fronto-parallel component in the image, we compute the displacement of each row from a reference frame by our novel phase matching approach in the complex-valued Shearlet transform domain. So far the only way to process rolling shutter video for vibration extraction is with the Steerable Pyramid in a motion magnification framework. However, the Shearlet transform is well localized in scale, location and orientation, and hence better suited to vibration extraction than the Steerable Pyramid used in the high speed video approach. Using our rolling shutter approach, we manage to recover signals from 75Hz to 500Hz from videos of 30fps. We test our method by controlled experiments with a loudspeaker. We play sounds with certain frequency components and take videos of the loudspeaker's surface. Our approach recovers chirp signals as well as single frequency signals from rolling shutter videos. We also test with music and speech. Both experiments produce identifiable recovered audio.

This work describes the design and implementation details of a reliable group communication mechanism. The mechanism guarantees that messages will be received by all the operational members of the group or by none of them (atomicity). In addition, the sequence of messages will be the same at each of the recipients (order). The message ordering property can be used to simplify distributed database systems and distributed processing algorithms. The proposed mechanism continues to operate despite process, host and communication link failures (survivability). Survivability is essential in fault-tolerant applications. / Science, Faculty of / Computer Science, Department of / Graduate

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No / The application of computer vision in face processing remains an important research field. The aim of this chapter is to provide an up-to-date review of research efforts of computer vision scientist in facial image processing, especially in the areas of entertainment industry, surveillance, and other human computer interaction applications. To be more specific, this chapter reviews and demonstrates the techniques of visible facial analysis, regardless of specific application areas. First, the chapter makes a thorough survey and comparison of face detection techniques. It provides some demonstrations on the effect of computer vision algorithms and colour segmentation on face images. Then, it reviews the facial expression recognition from the psychological aspect (Facial Action Coding System, FACS) and from the computer animation aspect (MPEG-4 Standard). The chapter also discusses two popular existing facial feature detection techniques: Gabor feature based boosted classifiers and Active Appearance Models, and demonstrate the performance on our in-house dataset. Finally, the chapter concludes with the future challenges and future research direction of facial image processing.

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