DAVIS第七课：Feature Detection and Tracking with the Dynamic and Active-pixel Vision
第八课：Feature Detection and Tracking with the Dynamic and Active-pixel Vision 1.摘要 因为标准的相机以一种连续的时间间隔采样场景，所以他们并不提供后续帧之间盲区时间。 然而， 对于大多数高速运动的机器人和视觉应用中，在盲区时间内提供一种高速率测量更新是至关重要的。 DAVIS联合了标准相机和异步事件传感器， 能够解决上述难
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相关文章
- 1. VINS（二）Feature Detection and Tracking
- 2. DAVIS第四课：基于DAVIS的特征点检测和追踪
- 3. 论文阅读：《POI: Multiple Object Tracking with High Performance Detection and Appearance Feature 》
- 4. Bridging the Gap Between Detection and Tracking: A Unified Approach
- 5. Dynamic Channel Pruning Feature Boosting and Suppression
- 6. Vision and Image Course Project
- 7. 论文笔记：Integrated Object Detection and Tracking with Tracklet-Conditioned Detection
- 8. Fun with dynamicobject dynamic and the settings table
- 9. 学习笔记：LAB Feature with Feature-centric Cascade for Fast and Accurate Face Detection
- 10. RCNN：Rich feature hierarchies for accurate object detection and semantic segmentation