SpaceTime Environmental Image Information for Scene Understanding

Abstract

Approved for public release; distribuiton unlimited. ii REPORT DOCUMENTATION PAGEForm Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing the burden, to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. REPORT DATE (DD-MM-YYYY) April 20162. REPORT TYPE ARL-TR-7652 SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR'S ACRONYM(S) SPONSOR/MONITOR'S REPORT NUMBER(S) DISTRIBUTION/AVAILABILITY STATEMENTApproved for public release; distribution unlimited. SUPPLEMENTARY NOTES ABSTRACTThe interpretation of space-and time-varying environmental image information can pose serious challenges for rapid and robust scene understanding, particularly for problems of interest to the Army. Changing environmental conditions, such as illumination, precipitation, and vegetation, can obscure features, degrade object recognition, and modify saliency and image context. Current methods for scene understanding do not address elements of image information (and image context) affected by space-and time-changing environmental conditions, and as a result, important and meaningful features of the image data may be overlooked. In this report, we propose that it is important to incorporate space-and time-varying environmental image information from the very beginning of the data collection process so that the recorded images can be more effectively indexed and retrieved for operational use and analysis. This top-down approach not only provides a systematic characterization of the measured data for better scene description, but can also help the end user (Soldier) develop improved course of action strategies based on scene understanding (algorithms and analysis) incorporating battlefield environments changing in space and time.

Mission Driven Scene Understanding: Candidate Model Training and Validation

“…For example, important image features may be related to space-time coordinates, weather conditions and trends, visibility, terrain, scene descriptors, anomalies, and other salient features. [3][4][5] To explore the impact of dynamic environments on scene undersanding, we need a computational engine for scene exploration of new images. At this stage, we are evaluating different computational frameworks that may be useful to incorporate dynamic environments into mission driven scene understanding.…”