Jing LouChangzhou Vocational Institute of Mechatronic Technology · School of Information Engineering
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Citations since 2017
5 Research Items
Greetings! My name is Jing Lou (楼竞). I am an associate professor in the School of Information Engineering, Changzhou Vocational Institute of Mechatronic Technology (CZIMT). My research interests include image processing, computer vision, and deep learning. Specifically, my current research focuses on salient/co-salient object detection. For more details, please refer to my personal homepage http://www.loujing.com/
In this paper, we will investigate the contribution of color names for the task of salient object detection. An input image is first converted to color name space, which is consisted of 11 probabilistic channels. By exploiting a surroundedness cue, we obtain a saliency map through a linear combination of a set of sequential attention maps. To overc...
Receiving growing attention for its various applications during the last few years, multi-object tracking remains a complex and challenging problem. Conventional grid-based tracking method is an efficient and effective method to tackle multi-object tracking, whose performance can be further boosted by intuitively taking into account the appearance...
Road Detection is a basic task in automated driving field, in which 3D lidar data is commonly used recently. In this paper, we propose to rearrange 3D lidar data into a new organized form to construct direct spatial relationship among point cloud, and put forward new features for real-time road detection tasks. Our model works based on two prerequi...
In this paper, a bottom-up and data-driven model is introduced to detect co-salient objects from an image pair. Inspired by the biologically-plausible across-scale architecture, we propose a multi-layer fusion algorithm to extract conspicuous parts from an input image. At each layer, two existing saliency models are first combined to obtain an init...
In this paper, we will address the issue of detecting small target in a color image from the perspectives of both stability and saliency. First, we consider small target detection as a stable region extraction problem. Several stability criteria are applied to generate a stability map, which involves a set of locally stable regions derived from seq...
Saliency detection is widely used in many visual applications like image segmentation, object recognition and classification. In this paper, we will introduce a new method to detect salient objects in natural images. The approach is based on a regional principal color contrast modal, which incorporates low-level and medium-level visual cues. The me...