Event-Based Moving Object Detection and Tracking

@article{Mitrokhin2018EventBasedMO,
  title={Event-Based Moving Object Detection and Tracking},
  author={Anton Mitrokhin and Cornelia Ferm{\"u}ller and Chethan Parameshwara and Yiannis Aloimonos},
  journal={2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year={2018},
  pages={1-9}
}
Event-based vision sensors, such as the Dynamic Vision Sensor (DVS), are ideally suited for real-time motion analysis. The unique properties encompassed in the readings of such sensors provide high temporal resolution, superior sensitivity to light and low latency. These properties provide the grounds to estimate motion efficiently and reliably in the most sophisticated scenarios, but these advantages come at a price - modern event-based vision sensors have extremely low resolution, produce a… 

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References

SHOWING 1-10 OF 29 REFERENCES
Feature detection and tracking with the dynamic and active-pixel vision sensor (DAVIS)
TLDR
This work presents the first algorithm to detect and track visual features using both the frames and the event data provided by the DAVIS, a novel vision sensor which combines a standard camera and an asynchronous event-based sensor in the same pixel array.
Independent motion detection with event-driven cameras
TLDR
The method detects and tracks corners in the event stream and learns the statistics of their motion as a function of the robot's joint velocities when no independently moving objects are present, and is robust to changes in speed of both the head and the target.
Event-Based Visual Inertial Odometry
TLDR
This paper presents the first algorithm to fuse a purely event-based tracking algorithm with an inertial measurement unit, to provide accurate metric tracking of a cameras full 6dof pose.
Real-Time Clustering and Multi-Target Tracking Using Event-Based Sensors
TLDR
This work presents a real-time clustering technique that takes advantage of the unique properties of event-based vision sensors that redefines the well-known mean-shift clustering method using asynchronous events instead of conventional frames.
Contour Motion Estimation for Asynchronous Event-Driven Cameras
TLDR
Algorithms are presented for the estimation of accurate contour motion from local spatio-temporal information for two camera models: the dynamic vision sensor (DVS), which asynchronously records temporal changes of the luminance, and a family of new sensors which combine DVS data with intensity signals.
Spatiotemporal multiple persons tracking using Dynamic Vision Sensor
TLDR
An algorithm for spatiotemporal tracking that is suitable for Dynamic Vision Sensor is introduced and the problem of multiple persons tracking in the occurrence of high occlusions is addressed.
Real-time panoramic tracking for event cameras
TLDR
This work proposes a direct camera tracking formulation, similar to state-of-the-art in visual odometry, and shows that the minimal information needed for simultaneous tracking and mapping is the spatial position of events, without using the appearance of the imaged scene point.
Embedded Vision System for Real-Time Object Tracking using an Asynchronous Transient Vision Sensor
  • M. Litzenberger, C. Posch, H. Garn
  • Computer Science
    2006 IEEE 12th Digital Signal Processing Workshop & 4th IEEE Signal Processing Education Workshop
  • 2006
TLDR
An algorithm for object tracking with 1 millisecond timestamp resolution of the AER data stream is presented and the potential of the proposed algorithm for people tracking is shown.
Simultaneous Mosaicing and Tracking with an Event Camera
TLDR
This work shows for the first time that an event stream, with no additional sensing, can be used to track accurate camera rotation while building a persistent and high quality mosaic of a scene which is super-resolution accurate and has high dynamic range.
Asynchronous Event-Based Multikernel Algorithm for High-Speed Visual Features Tracking
This paper presents a number of new methods for visual tracking using the output of an event-based asynchronous neuromorphic dynamic vision sensor. It allows the tracking of multiple visual features
...
1
2
3
...