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A Biologically Inspired Vision-Based Approach for Detecting Multiple Moving Objects in Complex Outdoor Scenes

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Abstract

In the human brain, independent components of optical flows from the medial superior temporal area are speculated for motion cognition. Inspired by this hypothesis, a novel approach combining independent component analysis (ICA) with principal component analysis (PCA) is proposed in this paper for multiple moving objects detection in complex scenes—a major real-time challenge as bad weather or dynamic background can seriously influence the results of motion detection. In the proposed approach, by taking advantage of ICA’s capability of separating the statistically independent features from signals, the ICA algorithm is initially employed to analyze the optical flows of consecutive visual image frames. As a result, the optical flows of background and foreground can be approximately separated. Since there are still many disturbances in the foreground optical flows in the complex scene, PCA is then applied to the optical flows of foreground components so that major optical flows corresponding to multiple moving objects can be enhanced effectively and the motions resulted from the changing background and small disturbances are relatively suppressed at the same time. Comparative experimental results with existing popular motion detection methods for challenging imaging sequences demonstrate that our proposed biologically inspired vision-based approach can extract multiple moving objects effectively in a complex scene.

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Acknowledgments

This research is supported by The Royal Society of Edinburgh (RSE) and The National Natural Science Foundation of China (NNSFC) under the RSE-NNSFC Joint Project (2012–2014) [Grant Number 61211130309] with Anhui University, China, and the ‘Sino-UK Higher Education Research Partnership for Ph.D. Studies’ Joint Project (2013–2015) funded by the British Council China and The China Scholarship Council (CSC). Amir Hussain and Erfu Yang are also funded, in part, by the UK Engineering and Physical Sciences Research Council (EPSRC) [Grant Number EP/I009310/1] and the RSE-NNSFC joint project (2012–2014) [Grant Number 61211130210] with Beihang University, China. We also thank Dr. Andrew Abel for providing some good suggestions for this paper.

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Authors and Affiliations

  1. School of Computer Science and Technology, Anhui University, Hefei, 230601, China

    Zhengzheng Tu, Aihua Zheng & Bin Luo

  2. Division of Computing Science and Mathematics, University of Stirling, Stirling, FK9 4LA, UK

    Erfu Yang & Amir Hussain

  3. Key Lab of Industrial Image Processing and Analysis of Anhui Province, Hefei, 230039, China

    Zhengzheng Tu & Bin Luo

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  1. Zhengzheng Tu
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  2. Aihua Zheng
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  3. Erfu Yang
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  4. Bin Luo
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  5. Amir Hussain
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Correspondence to Bin Luo.

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Tu, Z., Zheng, A., Yang, E. et al. A Biologically Inspired Vision-Based Approach for Detecting Multiple Moving Objects in Complex Outdoor Scenes. Cogn Comput 7, 539–551 (2015). https://doi.org/10.1007/s12559-015-9318-z

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  • DOI: https://doi.org/10.1007/s12559-015-9318-z

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