Abstract-Salient object detection has been attracting a lot of interest, and recently various heuristic computational models have been designed. In this paper, we formulate saliency map computation as a regression problem. Our method, which is based on multi-level image segmentation, utilizes the supervised learning approach to map the regional feature vector to a saliency score. Saliency scores across multiple layers are finally fused to produce the saliency map. The contributions lie in two-fold. One is that we propose a discriminate regional feature integration approach for salient object detection. Compared with existing heuristic models, our proposed method is able to automatically integrate high-dimensional regional saliency features and choose discriminative ones. The other is that by investigating standard generic region properties as well as two widely studied concepts for salient object detection, i.e., regional contrast and backgroundness, our approach significantly outperforms state-of-the-art methods on six benchmark datasets. Meanwhile, we demonstrate that our method runs as fast as most existing algorithms.

We developed an air pollutant emission inventory for marine vessels in the Shanghai Port in 2003. We estimated emissions under cruising and maneuvering conditions based on two categories of vessels: (1) vessels in the Outer Port, which enter the area following notification of the Shanghai Maritime Safety Administration, a division of the Ministry of Communications of P.R. China; and (2) vessels in internal waterways, which enter those waters following notification of the local Port Administration Centers. Vessels in the Outer Port consist of three subcategories: (1) international vessels that are engaged in foreign commerce; (2) domestic vessels traveling along the downstream portion of the Huangpu River; and (3) domestic vessels traveling along the coast. We also estimate emissions from vessels over 1000 DWT operating under hotelling conditions in the Outer Port. In 2003, the total number of calls was approximately 1.3 million, of which 57% is attributed to vessels in internal waterways and 43% to vessels in the Outer Port. Total marine emissions for NOx, SO2, PM, HC, and CO2 in 2003 are estimated to be 58,160, 51,180, 6960, 4560, and 3,012,800 tons, respectively. Emissions are allocated to 1 km x 1 km grid cells for the 129 km x 102 km Shanghai Port study domain.

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