Light sources’ position calibration is critical to photometric stereo. This paper presents a method for the light source position calibration based on a standard block. Unlike prior works that use mirror spheres, we use a calibration target consisting of a flat plane and a standard block placed on the plane with known length. By analyzing and reasoning the shadow produced by the standard block under a fixed light, we find that the relations of shadow and light conform to the principle of trigonometric geometry. The near light source’s position can be obtained according to the position relationship between the line segment and the inflection point in the shadow. Compared with other methods, our method is convenient and fast, and has better results.
In recent years, ocean front tracking is of vital importance in ocean-related research, and many algorithms have been proposed to identify ocean fronts. However, all these methods focus on single frame ocean-front classification instead of ocean-front tracking. In this paper, we propose an ocean-front tracking dataset (OFTraD) and apply GoogLeNet inception network to track ocean fronts in video sequences. Firstly, the video sequence is split into image blocks, then the image blocks are classified into ocean-front and background by GoogLeNet inception network. Finally, the labeled image blocks are used to reconstruct the video sequence. Experiments show that our algorithm can achieve accurate tracking results.
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