With a Graded Relevance Feedback (GRF) algorithm, we refined the feature subset that enhances the retrieval performance according to the graded relevance of the ...

With a Graded Relevance Feedback (GRF) algorithm, we refined the feature subset that enhances the retrieval performance according to the graded relevance of the ...

With a Graded Relevance Feedback (GRF) algorithm, we refined the feature subset that enhances the retrieval performance according to the graded relevance of the ...

Mar 1, 2012 · With a Graded Relevance Feedback (GRF) algorithm, we refined the feature subset that enhances the retrieval performance according to the graded ...

Relevance feedback for human motion retrieval ... Retrieval of logically relevant 3D human motions by Adaptive Feature Selection with Graded Relevance Feedback.

Recommendations. Retrieval of logically relevant 3D human motions by Adaptive Feature Selection with Graded Relevance Feedback. A system that can retrieve ...

Relevance feedback is an effective tool to narrow the semantic gap and enhance the retrieval performance. ... This paper presents a novel boosting approach for ...

Sep 13, 2020 · Retrieval of logically relevant 3D human motions by adaptive feature selection with graded relevance feedback. Pattern Recognit. Lett. 2012 ...

A relevance feedback algorithm based on RankBoost for content-based motion data retrieval (CBMR) is presented and has two characteristics.

Tang JKT, Leung H. Retrieval of logically relevant 3D human motions by Adaptive Feature Selection with Graded Relevance Feedback Pattern Recognition Letters.