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Color When It Counts: Grayscale-Guided Online Triggering for Always-On Streaming Video Sensing
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Color When It Counts: Grayscale-Guided Online Triggering for Always-On Streaming Video Sensing

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arXiv:2603.22466v1 Announce Type: cross Abstract: Always-on sensing is essential for next-generation edge/wearable AI systems, yet continuous high-fidelity RGB video capture remains prohibitively expensive for resource-constrained mobile and edge platforms. We present a new paradigm for efficient streaming video understanding: grayscale-always, color-on-demand. Through preliminary studies, we discover that color is not always necessary. Sparse RGB frames suffice for comparable performance when

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Grayscale

Digital image having no color information

In digital photography, computer-generated imagery, and colorimetry, a grayscale (American English) or greyscale (Commonwealth English) image is one in which the value of each pixel holds no color information. Pixel values are typically stored in the range 0 to 255 (black to white). Grayscale images...

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Computer vision

Computerized information extraction from images

Computer vision tasks include methods for acquiring, processing, analyzing, and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g. in the form of decisions. "Understanding" in this context signifies th...

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Grayscale

Digital image having no color information

Computer vision

Computerized information extraction from images
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arXiv:2603.22466v1 Announce Type: cross Abstract: Always-on sensing is essential for next-generation edge/wearable AI systems, yet continuous high-fidelity RGB video capture remains prohibitively expensive for resource-constrained mobile and edge platforms. We present a new paradigm for efficient streaming video understanding: grayscale-always, color-on-demand. Through preliminary studies, we discover that color is not always necessary. Sparse RGB frames suffice for comparable performance when
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