IRIM at TRECVID 2014: Semantic indexing and instance search

Our system proposes a simple scheme that combines two person recognition methods and two location recog- nition methods, performs a late fusion on each type individually, and applies

Then, by analyzing the value similarity of every instance pair in training set, njuLink finds some property pairs named discriminative property pairs, which have the ability to

The aim was to find the images that correspond to the same individual whale; and the basic idea was to create the mathematical representation of each image based on visual

Extracted features from region and sub-image blocks segmentation of video shots key-frames are described via IVSM signature (Image Vector Space Model) in order to have a compact

Considering only the results in table 7 (2013, 2014 and 2015 test sets), with and without I-frames, all of en- gineered features, temporal re-scoring and conceptual feed back do

The remainder of this paper briefly describes the descriptors that we have been using, the training and the various fusion schemes, and the content of the submitted runs; and the

Hierarchical fusion with multiple descriptor variants and multiple classifier variants was used and optimized for the semantic indexing task.. We made several ex- periment in order

Hierarchical fusion with multiple descriptor variants and multiple classifier variants was used and optimized for the semantic indexing task.. We made several ex- periment in order