Semi-automatic video object segmentation using LVQ with color and spatial features

Hariadi Mochamad, Hui Chien Loy, Takafumi Aoki

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


This paper presents a semi-automatic algorithm for video object segmentation. Our algorithm assumes the use of multiple key video frames in which a semantic object of interest is defined in advance with human assistance. For video frames between every two key frames, the specified video object is tracked and segmented automatically using Learning Vector Quantization (LVQ). Each pixel of a video frame is represented by a 5-dimensional feature vector integrating spatial and color information. We introduce a parameter K to adjust the balance of spatial and color information. Experimental results demonstrate that the algorithm can segment the video object consistently with less than 2% average error when the object is moving at a moderate speed.

Original languageEnglish
Pages (from-to)1553-1560
Number of pages8
JournalIEICE Transactions on Information and Systems
Issue number7
Publication statusPublished - 2005 Jul


  • Learning vector quantization
  • MPEG
  • Object extraction
  • Object segmentation
  • Video processing


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