Feature Sharing and Integration for Cooperative Cognition and Perception with Volumetric Sensors
Feature Sharing and Integration for Cooperative Cognition and Perception with Volumetric Sensors
复制标题
使用体积传感器进行协作认知和感知的功能共享和集成
DOI：
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Hongsheng Lu
中科院分区：
文献类型：
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作者：
Ehsan Emad Marvasti;Arash Raftari;Y. P. Fallah;Rui Guo;Hongsheng Lu
计算和通信系统的最新进展导致了高性能神经网络和高速无线车辆通信网络的引入。于是，协作感知和认知等新技术应运而生，通过提供部分遮挡目标的检测和扩大传感范围的解决方案，解决了传感设备的固有局限性。然而，设计一个可靠的协作认知或感知系统需要解决有限的网络资源和不同来源共享的数据之间的差异所带来的挑战。在本文中，我们研究了不同协作感知技术的要求、局限性和性能，并对深度特征共享（DFS）的概念进行了深入分析。我们探索不同的协作对象检测设计，并根据平均精度评估它们的性能。我们使用 Volony 数据集进行实验研究。结果证实 DFS 方法对 GPS 噪声引起的定位误差明显不太敏感。此外，结果证明，在场景中添加更多合作参与者所带来的 DFS 方法的检测增益与原始信息共享技术相当，而 DFS 使设计更加灵活，以满足通信需求。
The recent advancement in computational and communication systems has led to the introduction of high-performing neural networks and high-speed wireless vehicular communication networks. As a result, new technologies such as cooperative perception and cognition have emerged, addressing the inherent limitations of sensory devices by providing solutions for the detection of partially occluded targets and expanding the sensing range. However, designing a reliable cooperative cognition or perception system requires addressing the challenges caused by limited network resources and discrepancies between the data shared by different sources. In this paper, we examine the requirements, limitations, and performance of different cooperative perception techniques, and present an in-depth analysis of the notion of Deep Feature Sharing (DFS). We explore different cooperative object detection designs and evaluate their performance in terms of average precision. We use the Volony dataset for our experimental study. The results confirm that the DFS methods are significantly less sensitive to the localization error caused by GPS noise. Furthermore, the results attest that detection gain of DFS methods caused by adding more cooperative participants in the scenes is comparable to raw information sharing technique while DFS enables flexibility in design toward satisfying communication requirements.
AVR：增强车辆现实
DOI：
10.1145/3210240.3210319
发表时间：
2018
期刊：
and Services
影响因子：
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作者：
Qiu, Hang;Ahmad, Fawad;Bai, Fan;Gruteser, Marco;Govindan, Ramesh
通讯作者：
Govindan, Ramesh