Leveraging motion saliency via frame differencing for enhanced object detection in videos

Lena Nans; Chelsea Mediavilla; Diego Marez; Shibin Parameswaran

doi:10.1117/12.2678373

13 June 2023 Leveraging motion saliency via frame differencing for enhanced object detection in videos

Lena Nans, Chelsea Mediavilla, Diego Marez, Shibin Parameswaran

Proceedings Volume 12527, Pattern Recognition and Tracking XXXIV; 125270V (2023) https://doi.org/10.1117/12.2678373
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States

Conference Poster

Abstract

Video sensors are ubiquitous in the realm of security and defense. Successive image data from those sensors can serve as an integral part of early-warning systems by drawing attention to suspicious anomalies. Using object detection, computer vision, and machine learning to automate some of those detection and classification tasks aids in maintaining a consistent level of situational awareness in environments with ever-present threats. Specifically, the ability to detect small objects in video feeds would help people and systems to protect themselves against far away or small hazards. This work proposes a way to accentuate features in video stills by subtracting pixels from surrounding frames to extract motion information. Features extracted from a sequence of frames can be used either alone, or that signal can be concatenated onto the original image to highlight a moving object of interest. Using a two-stage object detector, we explore the impacts of frame differencing on Drone vs. Bird videos from both stationary cameras as well as cameras that pan and zoom. Our experiments demonstrate that this algorithm is capable of detecting objects that move in a scene regardless of the state of the camera.

Citation Download Citation

Lena Nans, Chelsea Mediavilla, Diego Marez, and Shibin Parameswaran "Leveraging motion saliency via frame differencing for enhanced object detection in videos", Proc. SPIE 12527, Pattern Recognition and Tracking XXXIV, 125270V (13 June 2023); https://doi.org/10.1117/12.2678373

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