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Thus, simple linear combination with fixed weights between the spatial saliency map and the temporal saliency map may lead to unsatisfactory result.
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Specifically, for infrared video saliency detection, both the spatial saliency and temporal saliency are considered.
Then, the spatial saliency and temporal saliency are combined to compute the spatiotemporal saliency using an adaptive fusion strategy.
Afterwards, an adaptive combination scheme guided by mutual consistency is exploited to integrate these two maps to generate the spatial saliency map.
The approach combines the spatial saliency and the temporal saliency with fixed weight.
The spatial saliency map is computed from joint embedding of spatial and color cues.
Given a video, we first compute the spatial saliency map which adopts joint embedding of spatial and color cues.
The motion contrast in the scene is weak, so that the spatial saliency is dominant over the temporal saliency in the adaptive fusion scheme.
In the spatial attention model, the approach of joint embedding of spatial and color cues is adopted to compute the spatial saliency map.
In contrast, a higher weight is assigned to the spatial saliency map when the motion contrast is weak.
It is seen from the figure that the spatial saliency map does not highlight the salient object successfully.
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