Normalized classifier fusion for semantic visual concept detection

Abstract

In this paper, we describe our classifier fusion framework for the visual concept detections of NIST TREC-2002 Video Retrieval Benchmark. A normalized ensemble fusion is explored to improve overall performance by incorporating normalization of confidence scores, aggregation via combiner function, and an optimize selection. The normalized classifier fusion shows significant detection improvements for our visual concepts.