UCLA, UC Santa Barbara’s BioPACIFIC MIP earns renewed NSF support to accelerate AI-driven biobased materials innovation
Grant and Award Announcement
Updates every hour. Last Updated: 19-Nov-2025 02:11 ET (19-Nov-2025 07:11 GMT/UTC)
Since the era of film photography, capturing and documenting high-speed dynamic processes has been a longstanding pursuit in science and engineering. With the rise of solid-state imaging technologies such as charge-coupled devices (CCD) and complementary metal-oxide-semiconductor (CMOS) sensors, high-speed imaging has garnered increasing attention and become a cornerstone in fields such as aerospace, industrial inspection, and national defense.
Conventional imaging sensors primarily record two-dimensional (2D) image sequences that lack depth information. In recent years, the rapid progress in optoelectronic technologies has made 3D imaging and sensing one of the most dynamic and critical frontiers in optical metrology and information optics. Among these, Fringe Projection Profilometry (FPP) has emerged as a leading non-contact 3D surface measurement technique due to its high accuracy, flexible encoding, and wide applicability. Nevertheless, conventional structured-light 3D imaging techniques such as FPP always rely on a one-to-one synchronization between pattern projection and image acquisition, fundamentally limiting the system’s temporal resolution to the native frame rate of the imaging sensor. Current methods to increase speed often depend on high-refresh-rate hardware, which significantly increases system complexity and cost. This hardware bottleneck has become a major obstacle in advancing high-speed and ultra-high-speed 3D imaging.