J
Jana Kosecka
Researcher at George Mason University
Publications - 166
Citations - 10467
Jana Kosecka is an academic researcher from George Mason University. The author has contributed to research in topics: Object detection & Motion estimation. The author has an hindex of 45, co-authored 155 publications receiving 9087 citations. Previous affiliations of Jana Kosecka include Austrian Institute of Technology & University of Pennsylvania.
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End-to-end learning of keypoint detector and descriptor for pose invariant 3D matching
TL;DR: In this paper, a Siamese architecture augmented by a sampling layer and a novel score loss function is proposed for keypoint detection and representation for 3D depth maps or 3D scans, where the two can be jointly optimized towards task-specific objectives without a need for separate annotations.
Posted Content
Semantic Image Based Geolocation Given a Map
Arsalan Mousavian,Jana Kosecka +1 more
TL;DR: An approach for geo-locating a novel view and determining camera location and orientation using a map and a sparse set of geo-tagged reference views and evaluates the approach for building identification and geo-localization on a new challenging outdoors urban dataset exhibiting large variations in appearance and viewpoint.
Proceedings ArticleDOI
Real-time, ultrasound-based control of a virtual hand by a trans-radial amputee
TL;DR: Preliminary trials with a transradial amputee participant to assess amputation-induced changes in muscular geometry, dynamics, and imaging characteristics, and potentially elucidate necessary refinements to the viability of ultrasound imaging in able-bodied subjects.
Journal ArticleDOI
Visually guided navigation
TL;DR: In this article, a model of the environment which is suitable for global navigation using visual sensing is proposed, where the environment is represented in terms of a place graph, where nodes correspond to places and arcs have associated servoing strategies for moving from one place to another.
Journal ArticleDOI
Estimating Planar Surface Orientation Using Bispectral Analysis
Hany Farid,Jana Kosecka +1 more
TL;DR: A direct method for estimating the orientation of a plane from a single view under perspective projection, assuming that the underlying planar texture has random phase, and showing that the nonlinearities introduced by perspective projection lead to higher order correlations in the frequency domain.