Proceedings Article10.1109/APCCAS.2016.7803920
Edge-based moving object tracking algorithm for an embedded system
Kai Xiang Yang,Ming Hwa Sheu +1 more
- 01 Oct 2016
pp 153-155
8
TL;DR: This paper proposed an image target tracking algorithm that can process 1280 × 720 resolution video sequences and provide accurate image tracking in real time and implemented this object tracking method in the embedded platform to achieve real-time execution for experimental testing in a complex environment.
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Abstract: In this paper, we propose an image target tracking algorithm for an embedded platform. Our proposed can process 1280 × 720 resolution video sequences and provide accurate image tracking in real time. In the tracking algorithm, an adaptive local edge detection method is employed to extract the feature pixels of a tracked object. To reduce tracking errors, a region-based local binary pattern feature method was employed to describe the edge pixels of the tracked object. Finally, we implemented this object tracking method in the embedded platform to achieve real-time execution for experimental testing in a complex environment.
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Image Edge Detection Based on a Spatial General Autoregressive Model
Fei Hao,Chen Ruwen,Wang Fan,Chen Delin,Shi Jingjing,Yuntao Hu +5 more
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TL;DR: A new scheme for image edge detection based spatial general autoregressive model (SGAR) is proposed in this work, which takes into consideration the nonlinearity at both edges and non-edges.
References
A texture-based method for modeling the background and detecting moving objects
Marko Heikkilä,Matti Pietikäinen +1 more
TL;DR: A novel and efficient texture-based method for modeling the background and detecting moving objects from a video sequence that provides many advantages compared to the state-of-the-art.
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A survey of appearance models in visual object tracking
TL;DR: A detailed review of the existing 2D appearance models for visual object tracking can be found in this article, where the authors decompose the problem of appearance modeling into two different processing stages: visual representation and statistical modeling.
•Posted Content
A Survey of Appearance Models in Visual Object Tracking
TL;DR: This survey provides a detailed review of the existing 2D appearance models for visual object tracking and takes a module-based architecture that enables readers to easily grasp the key points ofVisual object tracking.
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Object Tracking via Partial Least Squares Analysis
TL;DR: An object tracking algorithm that learns a set of appearance models for adaptive discriminative object representation that exploits both the ground truth appearance information of the target labeled in the first frame and the image observations obtained online, thereby alleviating the tracking drift problem caused by model update.
Part-Based Pedestrian Detection and Feature-Based Tracking for Driver Assistance: Real-Time, Robust Algorithms, and Evaluation
Antonio Prioletti,Andreas Mogelmose,Paolo Grisleri,Mohan M. Trivedi,Alberto Broggi,Thomas B. Moeslund +5 more
TL;DR: The novelty of this system relies on the combination of a HOG part-based approach, tracking based on a specific optimized feature, and porting on a real prototype and offers high performance in terms of detection rate, false positives per hour, and frame rate.
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