Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision

Table 1

A representative success score (AUC) of SRE for different subsets divided based on main variation of the target object. Only the top 5 trackers are displayed for clarity.

Image attributes	Ranking
	The first	The second	The third	The fourth	The fifth
Fast motion ()	CDBN-10-2 (0.472)	Struck (0.451)	TLD (0.385)	CXT (0.348)	OAB (0.322)
Background clutter ()	CDBN-10-2 (0.414)	ASLA (0.410)	Struck (0.408)	SCM (0.387)	VTD (0.377)
Motion blur ()	CDBN-10-2 (0.530)	Struck (0.452)	TLD (0.392)	CXT (0.354)	DFT (0.325)
Deformation ()	CDBN-10-2 (0.451)	Struck (0.398)	ASLA (0.386)	DFT (0.364)	CPF (0.362)
Illumination variation ()	CDBN-10-2 (0.440)	ASLA (0.405)	Struck (0.396)	SCM (0.389)	VTS (0.378)
In-plane rotation ()	CDBN-10-2 (0.422)	CXT (0.410)	Struck (0.410)	ASLA (0.405)	SCM (0.399)
Low resolution ()	CDBN-10-2 (0.387)	Struck (0.360)	MTT (0.326)	OAB (0.311)	TLD (0.305)
Occlusion ()	CDBN-10-2 (0.441)	Struck (0.405)	SCM (0.398)	TLD (0.384)	LSK (0.384)
Out-of-plane rotation ()	CDBN-10-2 (0.427)	Struck (0.409)	ASLA (0.404)	SCM (0.396)	VTD (0.392)
Out of view ()	CDBN-10-2 (0.457)	Struck (0.421)	LOT (0.411)	TLD (0.407)	CPF (0.394)
Scale variation ()	CDBN-10-2 (0.441)	ASLA (0.440)	SCM (0.438)	Struck (0.395)	TLD (0.384)