An interdisciplinary team has developed an innovative camera system that is faster and more flexible in terms of lighting conditions than existing systems, allowing it to capture moving images of animals in their natural setting. Researchers introduced hardware and software tools for ecologists and filmmakers that can capture and display animal-perceived colors in motion. Different animal species possess unique sets of photoreceptors that are sensitive to a wide range of wavelengths, from ultraviolet to infrared, dependent on each animal's specific ecological needs. Some animals can even detect polarized light. So, every species will perceive color a bit differently. Honeybees and birds, for instance, are sensitive to UV light, which isn't visible to human eyes. However, the authors contend that current techniques for producing false color imagery can't quantify the colors animals see while in motion, an important factor since movement is crucial to how different animals communicate and navigate the world around them via color appearance and signal detection.
Multispectral photography takes a series of photos across various wavelengths (including UV and infrared) and stacks them into different color channels to derive camera-independent measurements of color. This method trades some accuracy for better spatial information and is well-suited for studying animal signals, for instance, but it only works on still objects, so temporal information is lacking. Researchers developed a camera system capable of producing high-precision animal-view videos that capture the full complexity of visual signals as they would be perceived by an animal in a natural setting. They combined existing methods of multispectral photography with new hardware and software designs. The camera records video in four color channels simultaneously (blue, green, red, and UV). Once that data has been processed into perceptual units, the result is an accurate video of how a colorful scene would be perceived by various animals, based on what we know about which photoreceptors they possess. The team's system predicts the perceived colors with 92 percent accuracy.
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