Learning Visual Odometry with a Convolutional Network
We present an approach to predicting velocity and direction changes from visual information (”visual odometry”) using an end-to-end, deep learning-based architecture. The architecture uses a single type of computational module and learning rule to extract visual motion, depth, and finally odometry information from the raw data. Representations of depth
Kishore Reddy Konda, Roland Memisevic
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CodedVO: Coded Visual Odometry
Autonomous robots often rely on monocular cameras for odometry estimation and navigation. However, the scale ambiguity problem presents a critical barrier to effective monocular visual odometry. In this paper, we present CodedVO, a novel monocular visual odometry method that overcomes the scale ambiguity problem by employing custom optics to physically
Sachin Shah +4 more
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AKG‐VO: Adaptive Keyframe Generation Method for Improving Visual Odometry in Autonomous Vehicles
Keyframe selection remains a critical challenge in visual odometry, significantly influencing overall system performance. Traditional approaches have primarily focused on identifying meaningful frames; however, in cases where the robot operates at high ...
Donghyun Lee +3 more
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Visual odometry of Rhinecanthus aculeatus depends on the visual density of the environment. [PDF]
Karlsson C +3 more
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A Generic Image Processing Pipeline for Enhancing Accuracy and Robustness of Visual Odometry. [PDF]
Sabry M +5 more
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Robust Visual Odometry Leveraging Mixture of Manhattan Frames in Indoor Environments. [PDF]
Yuan H, Wu C, Deng Z, Yin J.
europepmc +1 more source
An Unsupervised Monocular Visual Odometry Based on Multi-Scale Modeling. [PDF]
Zhi H, Yin C, Li H, Pang S.
europepmc +1 more source
RAUM-VO: Rotational Adjusted Unsupervised Monocular Visual Odometry. [PDF]
Cimarelli C +3 more
europepmc +1 more source
Stereo Event-Based Visual–Inertial Odometry
Event-based cameras are a new type of vision sensor in which pixels operate independently and respond asynchronously to changes in brightness with microsecond resolution, instead of providing standard intensity frames.
Kunfeng Wang +3 more
doaj +1 more source
Unsupervised Monocular Visual Odometry for Fast-Moving Scenes Based on Optical Flow Network with Feature Point Matching Constraint. [PDF]
Zhuang Y +4 more
europepmc +1 more source

