HOPBAS10K: A 98×98 Pixels CMOS Vision Sensor for Background Subtraction
Background subtraction is one of the first visual tasks in many video processing applications. In this work, we introduce a hardware adaptation of a top-ranked rule-based algorithm, the Pixel-Based Adaptive Segmenter (PBAS), implemented on an integrated circuit with on-focal plane processing. On average, our hardware-oriented PBAS (HO-PBAS) proposal features a similar algorithm performance to that of the original PBAS with the benefit of a reduced number of samples of the background model and linear equations, and thus a simpler overall model. This algorithm was implemented as a 98×98 pixels full-custom mixed-signal 180 nm standard CMOS vision sensor. This solution features in-pixel processing with resource sharing strategies and 47 μm pixel pitch. The in-pixel processing includes the whole algorithm data path along with image pre-processing. The assessment of our implementation through F-Measure metrics with images captured by our chip from the public dataset changedetection shown on a PC screen results in a decrease of performance of only 6.7% with respect to the software version of PBAS.
keywords: Background subtraction, CMOS Vision Sensors, PBAS, Mixed-signal
Publication: Article
1709114285585
February 28, 2024
/research/publications/hopbas10k-a-9898-pixels-cmos-vision-sensor-for-background-subtraction
Background subtraction is one of the first visual tasks in many video processing applications. In this work, we introduce a hardware adaptation of a top-ranked rule-based algorithm, the Pixel-Based Adaptive Segmenter (PBAS), implemented on an integrated circuit with on-focal plane processing. On average, our hardware-oriented PBAS (HO-PBAS) proposal features a similar algorithm performance to that of the original PBAS with the benefit of a reduced number of samples of the background model and linear equations, and thus a simpler overall model. This algorithm was implemented as a 98×98 pixels full-custom mixed-signal 180 nm standard CMOS vision sensor. This solution features in-pixel processing with resource sharing strategies and 47 μm pixel pitch. The in-pixel processing includes the whole algorithm data path along with image pre-processing. The assessment of our implementation through F-Measure metrics with images captured by our chip from the public dataset changedetection shown on a PC screen results in a decrease of performance of only 6.7% with respect to the software version of PBAS. - Daniel García Lesta, Diego Cabello Ferrer, Paula López Martínez, Víctor Manuel Brea Sánchez - 10.1109/JSEN.2024.3367169
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