Time-Resolved Far Infrared Light Transport Decomposition for Thermal Photometric Stereo.

IF 20.8 1区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

IEEE Transactions on Pattern Analysis and Machine Intelligence Pub Date : 2021-06-01 Epub Date: 2021-05-11 DOI:10.1109/TPAMI.2019.2959304

Kenichiro Tanaka, Nobuhiro Ikeya, Tsuyoshi Takatani, Hiroyuki Kubo, Takuya Funatomi, Vijay Ravi, Achuta Kadambi, Yasuhiro Mukaigawa

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引用次数: 5

Abstract

We present a novel time-resolved light transport decomposition method using thermal imaging. Because the speed of heat propagation is much slower than the speed of light propagation, the transient transport of far infrared light can be observed at a video frame rate. A key observation is that the thermal image looks similar to the visible light image in an appropriately controlled environment. This implies that conventional computer vision techniques can be straightforwardly applied to the thermal image. We show that the diffuse component in the thermal image can be separated, and therefore, the surface normals of objects can be estimated by the Lambertian photometric stereo. The effectiveness of our method is evaluated by conducting real-world experiments, and its applicability to black body, transparent, and translucent objects is shown.

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热光度立体的时间分辨远红外光输运分解。

提出了一种利用热成像技术进行时间分辨光输运分解的方法。由于热的传播速度比光的传播速度慢得多，因此可以在视频帧速率下观察到远红外光的瞬态传输。一个关键的观察结果是，在适当控制的环境中，热图像看起来与可见光图像相似。这意味着传统的计算机视觉技术可以直接应用于热图像。我们证明了热图像中的漫射分量是可以分离的，因此，物体的表面法线可以通过朗伯氏光度立体来估计。通过实际实验验证了该方法的有效性，并证明了该方法对黑体、透明和半透明物体的适用性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Pattern Analysis and Machine Intelligence 工程技术-工程：电子与电气

CiteScore

28.40

自引率

3.00%

发文量

885

审稿时长

8.5 months

期刊介绍： The IEEE Transactions on Pattern Analysis and Machine Intelligence publishes articles on all traditional areas of computer vision and image understanding, all traditional areas of pattern analysis and recognition, and selected areas of machine intelligence, with a particular emphasis on machine learning for pattern analysis. Areas such as techniques for visual search, document and handwriting analysis, medical image analysis, video and image sequence analysis, content-based retrieval of image and video, face and gesture recognition and relevant specialized hardware and/or software architectures are also covered.