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Jiamin Ye

dblp:10/497 · DBLP profile ↗
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3ranked-venue papers
2as first author
0since 2021 · last 2018
0000-0001-5061-6135ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 2 · 2 first-authorArtificial intelligence and machine learning · 1Graphics, computer vision, multimedia, augmented reality and games · 1

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.

Computer graphics and multimedia
1 paper
Multimedia analysis and retrieval · 50% Image and video processing · 50%
Databases, data mining, and information retrieval
1 paper
Information retrieval · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video processing › image fusion
feature fusion		 0.012004
Aggregated feature retrieval for MPEG-7 via clustering · SIGIR 2004
Multimedia analysis and retrieval
video retrieval		 0.012004
Aggregated feature retrieval for MPEG-7 via clustering · SIGIR 2004
Information retrieval
document retrieval		 0.012004
Aggregated feature retrieval for MPEG-7 via clustering · SIGIR 2004

Methods — techniques the papers use, named apart from their topics

vector space model · 0.1clustering · 0.1tf-idf · 0.0TF-IDF · 0.0
YearPublicationVenuePosition
2018 A Stable Algebraic Camera Pose Estimation for Minimal Configurations of 2D/3D Point and Line Correspondences
Lipu Zhou, Jiamin Ye, Michael Kaess
 ACCV (4)2
2004 Aggregated feature retrieval for MPEG-7 via clustering
abstract
In this paper, we describe an approach to combining text and visual features from MPEG-7 descriptions of video. A video retrieval process is aligned to a text retrieval process based on the TF*IDF vector space model via clustering of low-level visual features. Our assumption is that shots within the same cluster are not only similar visually but also semantically, to a certain extent. Our experiments on the TRECVID2002 and TRECVID2003 collections show that adding extra meaning to a shot based on the shots from the same cluster is useful when each video in a collection contains a high proportion of similar shots, for example in documentaries.
Jiamin Ye, Alan F. Smeaton
 SIGIR1
2003 Aggregated Feature Retrieval for MPEG-7
Jiamin Ye, Alan F. Smeaton
 ECIR1