PicSOM experiments in TRECVID 2014 workshop notebook paper: Revision 1.16

Satoru Ishikawa, Markus Koskela, Mats Sjöberg, Rao Muhammad Anwer, Jorma Laaksonen, Erkki Oja

    Research output: Contribution to conferencePaperScientific


    Our experiments in TRECVID 2014 include successful participation in the Semantic Indexing (SIN) task and unsuccessful participation in the Multimedia Event Detection (MED) and Multimedia Event Recounting (MER) tasks. In semantic indexing, we participated in the main task only. We extended our last year's set of features with SIFT descriptors encoded with Fisher vectors and VLAD, and a total of 24 features based on convolutional neural network (CNN) activations. We also utilized hard negative mining to to acquire more relevant negative examples. We submitted the following four runs: • 4 MUMINPAPPAN: Baseline run matching the best PicSOM SIN submission in TRECVID 2013 • 3 HATTIFNATTAR: Run based on CNN features only, also including hard negative mining • 2 SNUSMUMRIKEN: Run with Fisher vector and VLAD features and the set of 24 CNN features included • 1 MÅRRAN: Run combining all features and hard negative mining The run 1 MÅRRAN obtained the highest MXIAP score of 0.2880. In the Multimedia Event Detection and Recounting task we tried to participate in the MED14-EvalFull search task, but failed.

    Original languageEnglish
    Publication statusPublished - 1 Jan 2020
    MoE publication typeNot Eligible
    EventInternational Workshop on Video Retrieval Evaluation - Orlando, United States
    Duration: 10 Nov 201412 Nov 2014


    WorkshopInternational Workshop on Video Retrieval Evaluation
    Abbreviated titleTRECVID
    Country/TerritoryUnited States


    Dive into the research topics of 'PicSOM experiments in TRECVID 2014 workshop notebook paper: Revision 1.16'. Together they form a unique fingerprint.

    Cite this