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Robust visual object tracking against occlusions and deformations is still very challenging task. To tackle these issues, existing Convolutional Neural Networks (CNNs) based trackers either fail to handle them or can just run in low speed. In this paper, we present a realtime tracker which is robust to occlusions and deformations based on a Region-based, Multi-Scale Fully Convolutional Siamese Network...
Convolutional neural network (CNN) based trackers have achieved significant performances in tracking recently. Most existing CNN-based trackers regard tracking as a classification or similarity searching problem. The two methods have their respective superiorities and limitations because of different supervised objectives. In this paper, we propose a multi-task CNN for visual tracking, not only fully...
Visual object tracking is one of the basic units in the construction of smart cities, which focuses on establishing a dynamic appearance model to represent and recognize the target in complex scenarios. In this paper, we consider visual object tracking as multiple local patches matching problem and design an online tracker based on correlation filter and binary descriptors. We integrate binary descriptors...
How to track an arbitrary object in video is one of the main challenges in computer vision, and it has been studied for decades. Based on hand-crafted features, traditional trackers show poor discriminability for complex changes of object appearance. Recently, some trackers based on convolutional neural network (CNN) have shown some promising results by exploiting the rich convolutional features....
Recently, graph ranking-based methods have been introduced to visual tracking and achieved promising results due to the local structure preserving property. However, existing graph ranking-based trackers use holistic templates to construct the graphs which makes the trackers sensitive to occlusions. In this paper, we propose a part-based multi-graph ranking algorithm for robust visual tracking. In...
With the development of science and technology, the technique of detecting regions of interest (ROI) plays an increasingly role in the field of the image analysis and processing. Human vision system actively seeks interesting regions in images to reduce the search export in tasks, such as object detection and recognition. Similarly, prominent actions in video sequences are more likely to attract human's...
A novel color correlogram based particle filter was proposed for an object tracking in visual surveillance. By using the color correlogram as object feature, spatial information is incorporated into object representation, which yields a reliable likelihood description of the observation and prediction for tracking the objects accurately. The capability of the tracker to tolerate appearance changes...
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