Demo Data from VLDB 2026 / reviewers in the wild / expert
Varun Asthana
dblp:278/2566
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
1 paper |
3D vision · 64% Legged, aerial and field robots · 36% |
Topics — the 7 heaviest of 7, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › 3D vision
depth estimation |
0.5 | 1 | 2021 | MorphEyes: Variable Baseline Stereo For Quadrotor Navigation · ICRA 2021 |
Robotics › Legged, aerial and field robots › rough terrain locomotion
gap crossing |
0.5 | 1 | 2021 | MorphEyes: Variable Baseline Stereo For Quadrotor Navigation · ICRA 2021 |
Robotics › Legged, aerial and field robots › aerial robots › UAV navigation
quadrotor navigation |
0.5 | 1 | 2021 | MorphEyes: Variable Baseline Stereo For Quadrotor Navigation · ICRA 2021 |
Computer vision › 3D vision › depth estimation
stereo depth estimation |
0.5 | 1 | 2021 | MorphEyes: Variable Baseline Stereo For Quadrotor Navigation · ICRA 2021 |
Computer vision › 3D vision › stereo vision
variable baseline stereo |
0.5 | 1 | 2021 | MorphEyes: Variable Baseline Stereo For Quadrotor Navigation · ICRA 2021 |
Computer vision › 3D vision
camera calibration |
0.1 | 1 | 2021 | MorphEyes: Variable Baseline Stereo For Quadrotor Navigation · ICRA 2021 |
Computer vision › 3D vision › camera calibration
stereo calibration |
0.1 | 1 | 2021 | MorphEyes: Variable Baseline Stereo For Quadrotor Navigation · ICRA 2021 |
Methods — techniques the papers use, named apart from their topics
on-the-fly baseline adaptation · 0.5interpolation of calibration parameters · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | MorphEyes: Variable Baseline Stereo For Quadrotor NavigationabstractMorphable design and depth-based visual control are two upcoming trends leading to advancements in the field of quadrotor autonomy. Stereo-cameras have struck the perfect balance of weight and accuracy of depth estimation but suffer from the problem of depth range being limited and dictated by the baseline chosen at design time. In this paper, we present a framework for quadrotor navigation based on a stereo camera system whose baseline can be adapted on-the-fly. We present a method to calibrate the system at a small number of discrete baselines and interpolate the parameters for the entire baseline range. We present an extensive theoretical analysis of calibration and synchronization errors. We showcase three different applications of such a system for quadrotor navigation: (a) flying through a forest, (b) flying through an unknown shaped/location static/dynamic gap, and (c) accurate 3D pose detection of an independently moving object. We show that our variable baseline system is more accurate and robust in all three scenarios. To our knowledge, this is the first work that applies the concept of morphable design to achieve a variable baseline stereo vision system on a quadrotor. Nitin J. Sanket, Chahat Deep Singh, Varun Asthana, Cornelia Fermüller, Yiannis Aloimonos |
ICRA | 3 |