Soldier Centric Imaging via Computational Cameras (SCENICC) | Apply Online

Opportunity Summary:

The Soldier Centric Imaging via Computational Cameras (SCENICC) opportunity is a DARPA Defense Sciences Office Broad Agency Announcement focused on pushing soldier-worn or soldier-scale imaging and sensing into a new class of ultra low size, weight, and power (SWaP) systems. The core idea is to move beyond traditional camera design by fully leveraging computational imaging, meaning that some of the capability normally achieved with bulky optics and hardware is instead achieved through computation, novel sensors, and co-designed algorithms. DARPA is looking for proposals that combine emerging imaging technologies with advanced processing to produce persistent and multi-functional Intelligence, Surveillance, and Reconnaissance (ISR) capabilities that can operate at the individual warfighter level. The program emphasis is on improving awareness and operational effectiveness while also enhancing security and survivability, implying solutions that can help soldiers see, detect, identify, and understand threats and surroundings with less burden and greater reliability than conventional systems.

From a technical standpoint, SCENICC highlights the “computational cameras” paradigm: imaging systems where optics, sensors, and algorithms are designed together so the final image or extracted information is the product of both physical capture and computational reconstruction or interpretation. In practice, this often points toward concepts such as coded apertures, novel lens designs, multiplexed or compressed sensing approaches, unconventional focal plane arrays, on-sensor or near-sensor processing, and algorithms that can reconstruct useful imagery or scene understanding from measurements that may not resemble a standard photograph. The emphasis on persistent and multi-functional ISR suggests DARPA’s interest in systems that can stay on for long periods, operate in real-world soldier conditions, and possibly support multiple modes or mission sets (for example, combining wide-area situational awareness with targeted recognition, or combining imaging with other sensing modalities) without imposing the usual SWaP penalties of stacking separate sensors and optics.

Administratively, this was posted as Funding Opportunity Number DARPA BAA 11-26, titled “Soldier Centric Imaging via Computational Cameras (SCENICC),” under the Science and Technology and other Research and Development activity category. The opportunity used multiple possible funding instruments, including cooperative agreements, grants, other procurement contracts, reflecting DARPA’s typical flexibility in structuring awards based on the nature of the work and performer relationship. The CFDA number listed is 12.910 (Research and Technology Development), and there was no cost sharing or matching requirement, which generally lowers barriers for participation and encourages proposing ambitious R&D without requiring the proposer to contribute funds.

In terms of timing and lifecycle, the opportunity was posted on December 22, 2010, with a closing date of March 9, 2011, and an archive date of May 9, 2011. Eligibility is described as unrestricted, meaning the solicitation was open to a broad range of potential performers (such as companies, universities, nonprofits, and other entities), subject to any additional eligibility details that might have been contained in the full announcement text. The announcement references an attached document (DARPA BAA 11-26) as the authoritative source for full technical areas, submission requirements, evaluation criteria, and administrative conditions. For access issues, DARPA provided a BAA Coordinator contact, which is typical for DARPA BAAs where the detailed program structure, milestones, and proposal instructions are contained in the full PDF announcement rather than the summary listing.

Overall, SCENICC can be read as DARPA seeking a step-change in what a soldier can carry and use for ISR: not just smaller versions of existing cameras, but fundamentally different imaging architectures that trade traditional optical complexity for computational sophistication, enabling lighter, lower-power, and more capable sensing systems that can meaningfully improve warfighter decision-making and survivability in the field.

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