Ucf-Crcv At Trecvid 2015: Semantic Indexing

Abstract

This paper describes the system we used for the main task of Semantic INdexing (SIN) at TRECVID 2015. Our system uses a five-stage processing pipeline including feature extraction, pooling, encoding, classification and reranking. We employed CNN-based representations, as well as Dense and Root SIFTs as features for our system. We also report results of our experiments with SentiBank features and data augmentation techniques that did not contribute to the performance of the final system. Our second run ‘Rostam’ achieved an infAP of 26.67% on the 30 concepts evaluated for SIN 2015.

Publication Date

1-1-2015

Publication Title

2015 TREC Video Retrieval Evaluation, TRECVID 2015

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

Socpus ID

85044180429 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85044180429

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