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Third, sound is a vibration that travels through a medium, like a gas, a liquid or a solid object. A sound's source is an object that moves or changes shape very rapidly. For example, if you strike a bell, the bell vibrates in the air. As one side of the bell moves out, it pushes the air molecules next to it, increasing the pressure in that region of the air. This area of higher pressure is a compression. As the side of the bell moves back in, it pulls the molecules apart, creating a lower-pressure region called a rarefaction. The bell then repeats the process, creating a repeating series of compressions and rarefactions. Each repetition is one wavelength of the sound wave. The sound wave travels as the moving molecules push. Pull the molecules around them. Each molecule moves the one next to it in turn. Without this movement of molecules, the sound could not travel, which is why there is no sound in a vacuum.|The development of visual object tracking has continued for decades. Recent years, as the wide accessibility of the low-cost RGBD sensors, the task of visual object tracking on RGB-D videos has drawn much attention. Compared to conventional RGB-only tracking, the RGB-D videos can provide more information that facilitates objecting tracking in some complicated scenarios. The goal of this review is to summarize the relative knowledge of the research filed of RGB-D tracking. To be specific, we will generalize the related RGB-D tracking benchmarking datasets as well as the corresponding performance measurements. Besides, the existing RGB-D tracking methods are summarized in the paper. Moreover, we discuss the possible future direction in the field of RGB-D tracking. Visual object tracking, as a fundamental research topic in computer vision and pattern recognition, aims to automatically predict the state of an object of interest in each frame of a video. Conventional visual object tracking mainly focus on RGB videos captured by a monocular camera.




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