论文标题
HMM引导的框架查询带宽受限的视频搜索
HMM-guided frame querying for bandwidth-constrained video search
论文作者
论文摘要
我们设计了一个代理，以在带宽约束下搜索存储在远程服务器上的视频中感兴趣的框架。使用卷积神经网络来评分单个帧和隐藏的马尔可夫模型来传播跨帧的预测，我们的代理可以准确地基于稀疏的，策略性地采样的框架来确定感兴趣的时间区域。在ImageNet-VID数据集的一个子集中，我们证明，使用隐藏的Markov模型在帧分数之间插值允许省略98％帧的请求，而不会损害利益框架分类精度。
We design an agent to search for frames of interest in video stored on a remote server, under bandwidth constraints. Using a convolutional neural network to score individual frames and a hidden Markov model to propagate predictions across frames, our agent accurately identifies temporal regions of interest based on sparse, strategically sampled frames. On a subset of the ImageNet-VID dataset, we demonstrate that using a hidden Markov model to interpolate between frame scores allows requests of 98% of frames to be omitted, without compromising frame-of-interest classification accuracy.
