  This work addresses the joint object discovery problem in videos while
utilizing multiple object-related cues. In contrast to the usual spatial fusion
approach, a novel appearance fusion approach is presented here. Specifically,
this paper proposes an effective fusion process of different GMMs derived from
multiple cues into one GMM. Much the same as any fusion strategy, this approach
also needs some guidance. The proposed method relies on reliability and
consensus phenomenon for guidance. As a case study, we pursue the "video
co-localization" object discovery problem to propose our methodology. Our
experiments on YouTube Objects and YouTube Co-localization datasets demonstrate
that the proposed method of appearance fusion undoubtedly has an advantage over
both the spatial fusion strategy and the current state-of-the-art video
co-localization methods.
