Xiao Ma's research while affiliated with Harbin Institute of Technology Shenzhen Graduate School and other places

Publications (5)

Article
Full-text available
Discriminative methods have been widely applied to construct the appearance model for visual tracking. Most existing methods incorporate online updating strategy to adapt to the appearance variations of targets. The focus of online updating for discriminative methods is to select the positive samples emerged in past frames to represent the appearan...
Article
Full-text available
In the past years, discriminative methods are popular in visual tracking. The main idea of the discriminative method is to learn a classifier to distinguish the target from the background. The key step is the update of the classifier. Usually, the tracked results are chosen as the positive samples to update the classifier, which results in the fail...
Article
Full-text available
Visual tracking remains a challenging problem in computer vision due to the intricate variation of target appearances. Some progress made in recent years has revealed that correlation filters, which formulate the tracking process by creating a regressor in the frequency domain, have achieved remarkable experimental results on a large amount of vide...

Citations

... In order to improve the tracking performance, it is required to develop optimal appearance model of object targets [35,36]. Most of the existing object appearance models can be can be classified into two camps: appearance model based on conventional hand-crafted feature [24,25,27], and appearance model based on CNN feature [13,23,34]. ...
... For a single object tracking, an arbitrary interested object can be selected as the target, which is initialized with a bounding box in the initial frame, and the tracker is going to locate the target in the following each frame [35]. Visual object tracking has been studied extensively during the past decades [18,40,41] and has been made great progress in recent years [12,19,20]. Despite several advanced approaches, visual object tracking is still regarded as a challenging task due to various reasons: occlusion (heavy occlusion, short-time complete occlusion), deformation (object posture, shape, scale, and appearance change), abrupt motion, illumination change, motion blur caused by camera moving, fast motion, in-plane rotation, out-of-plane rotation, out-of-view, background clutters, low resolution, and other disturbing factors etc [1,7]. ...
... Salient object detection (SOD) aims to achieve a unique, clear edge, completed object area which mostly can attract human visual attention. The SOD usually acts as an important role in the area of computer vision, such as object importance [1], visual object tracking [2,3], visual perception [4], contour 5 detection [5,6], motion detection [7,8], image denoising [9], and visual tracking [10,11,12,13] etc. Although some achievements have been obtained for SOD in the past, it is still a challenge problem in the community. ...