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HATS: Histograms of Averaged Time Surfaces for Robust Event-Based Object Classification
TLDR
This paper introduces a novel event-based feature representation together with a new machine learning architecture that uses local memory units to efficiently leverage past temporal information and build a robust event- based representation and releases the first large real-world event- Based object classification dataset.
Event-Based Visual Flow
TLDR
This paper introduces a framework to estimate visual flow from the local properties of events' spatiotemporal space and shows that precise visual flow orientation and amplitude can be estimated using a local differential approach on the surface defined by coactive events.
HOTS: A Hierarchy of Event-Based Time-Surfaces for Pattern Recognition
TLDR
The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood and it is demonstrated that this concept can robustly be used at all stages of an event-based hierarchical model.
Asynchronous frameless event-based optical flow
TLDR
The paper shows that current limitations of optical flow computation can be overcome by using event-based visual acquisition, where high data sparseness and high temporal resolution permit the computation of Optical flow with micro-second accuracy and at very low computational cost.
HFirst: A Temporal Approach to Object Recognition
TLDR
This paper introduces a spiking hierarchical model for object recognition which utilizes the precise timing information inherently present in the output of biologically inspired asynchronous address event representation (AER) vision sensors to show not only how timing can be used in object recognition, but also how it can in fact simplify computation.
Multiplex Cell and Lineage Tracking with Combinatorial Labels
TLDR
This approach allows us to track neural progenitor's descent during pre- and postnatal neurogenesis or perinatal gliogenesis in long-term experiments and opens new avenues for clonal and functional analysis in varied experimental models and contexts.
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 Binocular Stereo Matching
TLDR
It is shown that matching on the timing of the visual events provides a new solution to the real-time computation of 3-D objects when combined with geometric constraints using the distance to the epipolar lines.
Asynchronous visual event-based time-to-contact
TLDR
This paper introduces a fast obstacle avoidance method based on the output of an asynchronous event-based time encoded imaging sensor that is validated indoor on a mobile robot, showing that event- based sensing offers new perspectives for mobile robotics sensing.
Neuromorphic Event-Based Generalized Time-Based Stereovision
TLDR
This paper introduces a fully time-based solution to stereovision using the high temporal resolution of neuromorphic asynchronous event-based cameras and introduces a formulation that does not require to build local frames from the luminances which can be costly to implement.
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