标题： 内容感知的凝视相机用于多目标跟踪 显示英文标题

标题： Content-Aware Foveated Camera for Multi-Target Tracking

摘要： 现代图像传感器提供大量的时空带宽，但无差别采集常常会超出存储、计算和后续感知的能力。 我们提出一种内容感知的多视点相机，能够动态重新分配感测和放大功能到多个感兴趣区域（ROIs）。 仅相位空间光调制器（SLM）作为固态、无惯性的光束转向和透镜元件，实现了每帧视场（FOV）的重新配置和内容感知的目标跟踪。 通过在视点之间交错帧，我们的系统在保持宽视场情境上下文的同时，以高频率刷新每个ROI，从而减少数据量而不降低任务性能。 我们构建了一个采用单SLM、单传感器架构的原型，并展示了其在多个视角下实时多目标跟踪和动态ROI维护的应用。 该方法为在采集循环中集成检测、跟踪和分割算法提供了一条通用路径，将工作负载从后期处理转移到智能捕捉。 显示英文摘要

摘要： Modern image sensors deliver substantial space-time bandwidth, yet indiscriminate acquisition often overwhelms memory, computation, and downstream perception. We present a content-aware, multi-foveated camera that dynamically reallocates sensing and magnification to multiple regions of interest (ROIs). A phase-only spatial light modulator (SLM) serves as a solid-state, inertia-free beam-steering and lens element, enabling per-frame field-of-view (FOV) reconfiguration and content-aware target tracking. By interleaving frames across foveae, our system preserves a wide-FOV situational context while refreshing each ROI at high rates, thereby reducing data volume without degrading task performance. We constructed a prototype employing single-SLM, single-sensor architecture and demonstrated its application in real-time multi-object tracking with dynamic ROI maintenance across multiple viewpoints. The approach offers a general pathway to integrate detection, tracking, and segmentation algorithms in the acquisition loop, shifting workload from post hoc processing to intelligent capture.