  Modern multi-object tracking (MOT) system usually involves separated modules,
such as motion model for location and appearance model for data association.
However, the compatible problems within both motion and appearance models are
always ignored. In this paper, a general architecture named as MIF is presented
by seamlessly blending the Motion integration, three-dimensional(3D) Integral
image and adaptive appearance feature Fusion. Since the uncertain pedestrian
and camera motions are usually handled separately, the integrated motion model
is designed using our defined intension of camera motion. Specifically, a 3D
integral image based spatial blocking method is presented to efficiently cut
useless connections between trajectories and candidates with spatial
constraints. Then the appearance model and visibility prediction are jointly
built. Considering scale, pose and visibility, the appearance features are
adaptively fused to overcome the feature misalignment problem. Our MIF based
tracker (MIFT) achieves the state-of-the-art accuracy with 60.1 MOTA on both
MOT16&17 challenges.
