Florida International University - University of Miami Trecvid 2016 Conference

Yan, Y, Pouyanfar, S, Guan, S et al. (2016). Florida International University - University of Miami Trecvid 2016 .

cited authors

  • Yan, Y; Pouyanfar, S; Guan, S; Tian, H; Ha, HY; Shyu, ML; Chen, SC; Chen, W; Chen, T; Chen, J

fiu authors

abstract

  • This paper demonstrates the framework and results from the team “Florida International University - University of Miami (FIU-UM)” in TRECVID 2016 [1] Ad-hoc Video Search (AVS) task [2]. The following two runs were submitted: • M D FIU UM.16 1: CNN features + linear SVM + concept scores combination type I • M D FIU UM.16 2: CNN features + linear SVM + concept scores combination type II In both runs, the features are first extracted by the CNN (Convolutional Neural Network) structure of AlexNet [3]. Then, using the linear SVM (Support Vector Machine) classifiers, the scores of each concept for the key frames are generated. For run 1 and run 2, the scores from the aforementioned model are combined in different ways for different queries. From the submission results, run 2 outperforms run 1. The submission details are listed as follows. • Class: M (Manually-assisted runs) • Training type: D (IACC & non-IACC non-TRECVID data) • Team ID: FIU-UM (Florida International University - University of Miami) • Year: 2016

publication date

  • January 1, 2016