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A Joint Intensity-Neuromorphic Event Imaging System With Bandwidth-Limited Communication Channel.

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    This study introduces an adaptive algorithm for object tracking that efficiently uses both intensity frames and neuromorphic events under limited data rates. Combining these data types significantly improves tracking accuracy compared to using intensity alone.

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    Area of Science:

    • Computer Vision
    • Robotics
    • Signal Processing

    Background:

    • Object tracking systems often face limitations due to bit rate constraints, especially on resource-constrained hardware like chips.
    • Utilizing both intensity frames and neuromorphic events offers potential for improved tracking but requires efficient data handling.

    Purpose of the Study:

    • To develop an adaptive multimodal algorithm for optimizing object tracking performance under bit rate constraints.
    • To create a joint intensity-neuromorphic event rate-distortion compression framework for efficient data allocation.

    Main Methods:

    • A quadtree (QT)-based compression scheme was developed for both intensity and event data.
    • An adaptive algorithm was designed to allocate bits optimally between intensity and events based on distortion and channel capacity.
    • A fusion framework was implemented on the host to enhance distorted data for improved detection and tracking.

    Main Results:

    • The proposed algorithm successfully optimizes object tracking under bit rate constraints.
    • Joint compression and fusion of intensity and event data enhanced tracking performance.
    • The system demonstrated improved Multiple Object Tracking Accuracy (MOTA) scores compared to intensity-only tracking.

    Conclusions:

    • The adaptive multimodal algorithm effectively balances data compression and tracking accuracy.
    • Combining intensity and neuromorphic event data provides superior object tracking performance in various scenarios.
    • This approach is suitable for computationally resource-constrained host-chip architectures.