title: Performance measures for video object segmentation and tracking.
abstract: We propose measures to evaluate quantitatively the performance of video object segmentation and tracking methods without ground-truth (GT) segmentation maps. The proposed measures are based on spatial differences of color and motion along the boundary of the estimated video object plane and temporal differences between the color histogram of the current object plane and its predecessors. They can be used to localize (spatially and/or temporally) regions where segmentation results are good or bad; and/or they can be combined to yield a single numerical measure to indicate the goodness of the boundary segmentation and tracking results over a sequence. The validity of the proposed performance measures without GT have been demonstrated by canonical correlation analysis with another set of measures with GT on a set of sequences (where GT information is available). Experimental results are presented to evaluate the segmentation maps obtained from various sequences using different segmentation approaches.
authors.affiliation: Momentum Digital Media Technology, Inc, Istanbul 80815, Turkey. cigdem@ieee.org
authors.forename: Ciğdem Eroğlu
authors.initials: CE
authors.lastname: Erdem
authors.forename: Bülent
authors.initials: B
authors.lastname: Sankur
authors.forename: A Murat
authors.initials: AM
authors.lastname: Tekalp
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003196:Computer Graphics; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D009068:Movement; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D012986:Software Validation; D013382:Subtraction Technique; D014741:Video Recording / Q000379:methods*