Object motion detection using information theoretic spatio-temporal saliency

Liu, Chang; Yuen, Pong C.; Qiu, Guoping

doi:10.1016/j.patcog.2009.02.002

Cited by 84 publications

(39 citation statements)

References 29 publications

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“…Applications of visual saliency models cover a range of dif-70 ferent areas; from low-level object detection and tracking [11,12], to more complex robot localisation and navigation [13]. Models of visual attention can vary on the basis of their processing characteristics, they can either take top-down factors into account (that relate to high-level cognitive factors) or bottom-up (called saliency") processing [6].…”

Section: Visual Saliency In Planetary Environmentsmentioning

confidence: 99%

Structure augmented monocular saliency for planetary rovers

Spiteri

Shaukat

Gao

2017

Robotics and Autonomous Systems

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Section: Visual Saliency In Planetary Environmentsmentioning

confidence: 99%

Structure augmented monocular saliency for planetary rovers

Spiteri

Shaukat

Gao

2017

Robotics and Autonomous Systems

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“…Most of the research works in motion segmentation have been attempted using the conventional background subtraction [5], statistical background subtraction [6][7][8][9][10], temporal differencing [11][12][13], optical flow [14] and hybrid [15][16][17][18][19][20][21] approaches.…”

Section: Literature Reviewmentioning

confidence: 99%

“…A method that combines temporal differencing with statistical correlation is proposed by Girisha and Murali [17] for motion segmentation. Some more hybrid methods are proposed in [15,16,[18][19][20][21] which use combination of motion based and spatio-temporal segmentation for segmenting the objects of interest.…”

Section: Literature Reviewmentioning

confidence: 99%

Cast and Self Shadow Segmentation in Video Sequences using Interval based Eigen Value Representation

Chandrajit¹,

Girisha²,

Vasudev³

et al. 2016

IJCA

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Tracking of motion objects in the surveillance videos is useful for the monitoring and analysis. The performance of the surveillance system will deteriorate when shadows are detected as moving objects. Therefore, shadow detection and elimination usually benefits the next stages. To overcome this issue, a method for detection and elimination of shadows is proposed. This paper presents a method for segmenting moving objects in video sequences based on determining the Euclidian distance between two pixels considering neighborhood values in temporal domain. Further, a method that segments cast and self shadows in video sequences by computing the Eigen values for the neighborhood of each pixel is proposed. The dual-map for cast and self shadow pixels is represented based on the interval of Eigen values. The proposed methods are tested on the benchmark IEEE CHANGE DETECTION 2014 dataset.

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“…In Ref. 33 proposed a BS algorithm based on spatio-temporal saliency using a center-surround framework, which is inspired by biological mechanisms of motion-based perceptual grouping. These methods have shown the potential of the HVS in moving object detection.…”

Section: Human Visual System-based Modelsmentioning

confidence: 99%

Improved visual background extractor using an adaptive distance threshold

Han¹,

Wang

2014

J. Electron. Imaging

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Abstract. Camouflage is a challenging issue in moving object detection. Even the recent and advanced background subtraction technique, visual background extractor (ViBe), cannot effectively deal with it. To better handle camouflage according to the perception characteristics of the human visual system (HVS) in terms of minimum change of intensity under a certain background illumination, we propose an improved ViBe method using an adaptive distance threshold, named IViBe for short. Different from the original ViBe using a fixed distance threshold for background matching, our approach adaptively sets a distance threshold for each background sample based on its intensity. Through analyzing the performance of the HVS in discriminating intensity changes, we determine a reasonable ratio between the intensity of a background sample and its corresponding distance threshold. We also analyze the impacts of our adaptive threshold together with an update mechanism on detection results. Experimental results demonstrate that our method outperforms ViBe even when the foreground and background share similar intensities. Furthermore, in a scenario where foreground objects are motionless for several frames, our IViBe not only reduces the initial false negatives, but also suppresses the diffusion of misclassification caused by those false negatives serving as erroneous background seeds, and hence shows an improved performance compared to ViBe.

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Object motion detection using information theoretic spatio-temporal saliency

Cited by 84 publications

References 29 publications

Structure augmented monocular saliency for planetary rovers

Structure augmented monocular saliency for planetary rovers

Cast and Self Shadow Segmentation in Video Sequences using Interval based Eigen Value Representation

Improved visual background extractor using an adaptive distance threshold

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