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Person re-identification, PhD Day 2011

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Riccardo Satta
Riccardo Satta

Awarded presentation of my research activity, PhD Day 2011, February 23th 2011, Cagliari, Italy. This presentation has been awarded as the best one of the track on information engineering. Want to know more? see my publications at http://prag.diee.unica.it/pra/ita/people/satta

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Exploiting Multiple Component Representations for Person Re-Identification Ph.D. candidate: Riccardo Satta Annual report, Year I
Outline ,[object Object],[object Object],[object Object],[object Object]
Introduction ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Main issues ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],figure 1 figure 4 figure 2 figure 3
Problem formulation ,[object Object],[object Object],[object Object],Descriptor generation MATCHING SCORE (similarity) Descriptor generation TEMPLATE PROBE T = Q T i
My contribution to this field ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Towards a Multiple Component Representation of the Human Body ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Towards a Multiple Component Representation of the Human Body ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],{ x 1 , … , x p } { x 1 , … , x p } { x 1 , … , x p } { x 1 , … , x p } { x 1 , … , x p } { x 1 , … , x p } { x 1 , … , x p } Object
Multiple Component Matching Framework ,[object Object],[object Object],[object Object],[object Object],[object Object],Example (4 parts)
Multiple Component Matching Framework ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
MCM Implementation ,[object Object],[object Object],[object Object],[object Object],[object Object],[1] M. Farenzena, L. Bazzani, A. Perina, V. Murino, and M. Cristani . Person re-identification by symmetry-driven accumulation of local features. In Proc. IEEE Conf. on Comp. Vision and Patt. Rec., 2010
MCM Implementation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
MCM Implementation ,[object Object],[object Object],[object Object]
MCM Implementation ,[object Object],[object Object],[object Object],[object Object],[object Object]
MCM Implementation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[2] Wang and J.-D. Zucker. Solving the multiple-instance problem: A lazy learning approach . In Proc. Int. Conf. Mach. Learn., 2000.
Evaluation ,[object Object],[object Object],[object Object],SDALF refers to the state-of-the art on this dataset [1] [1] M. Farenzena, L. Bazzani, A. Perina, V. Murino, and M. Cristani . Person re-identification by symmetry-driven accumulation of local features. In Proc. IEEE Conf. on Comp. Vision and Patt. Rec., 2010
Prototypes ,[object Object],[object Object]
Further developments ,[object Object],[object Object],[object Object],[object Object],Prototype 1 Prototype 2 Prototype N d 1 d 2 d N Dissimilarity representation
Further developments ,[object Object],[object Object],ID 1 ID 1 ID 2 ID 2 ID 3 ID 3
Thanks! ,[object Object]

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Person re-identification, PhD Day 2011

  • 1. Exploiting Multiple Component Representations for Person Re-Identification Ph.D. candidate: Riccardo Satta Annual report, Year I
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Notes de l'éditeur

  1. d is the euclidean distance between symmetric pixels HSV values (H, S, V all normalized between 0 and 1). C is normalized (in respect to the number of rows!)