Aggregating Sparse Binarized Local Features by Summing for Efficient 3D Model Retrieval

An effective and widespread approach for shape-based 3D model retrieval (3DMR) is to use a feature vector per 3D model obtained by aggregating, or pooling, a set of local features extracted from the 3D model. State-of-the-art feature aggregation algorithms, such as Fisher Vector (FV) coding [7] or S...

Celý popis

Podrobná bibliografia

Vydané v:	2016 IEEE Second International Conference on Multimedia Big Data (BigMM) s. 314 - 321
Hlavní autori:	Furuya, Takahiko, Ohbuchi, Ryutarou
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.04.2016
Predmet:	Big data binary feature Conferences feature aggregation feature encoding local feature Multimedia communication shape-based 3D model retrieval sparse coding
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!