Joint Spatial and Frequency Domain Motion Analysis

Ahuja, Narendra; Briassouli, Alexia

doi:10.1109/fgr.2006.68

Cited by 1 publication

(3 citation statements)

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“…The spatial motion information S(t) is obtained at time t by summing all values in S i,j (t) as follows (4) where r and c represent row and column of S respectively. However, motion extracted in spatial domain is not sensitive to diffuse phenomena [25]. For example, in case of global illumination changes, it does not work well.…”

Section: Motion Information Calculation In Spatial Domainmentioning

confidence: 99%

“…To overcome the problem of spatial motion calculation, motion information is calculated in frequency domain. Motion estimated in frequency domain has some advantages over spatial domain [25]. It is efficient for global changes of illumination and robust to motion estimation near object boundaries.…”

Section: Motion Estimation In Frequency Domainmentioning

confidence: 99%

“…All the values greater than T3 are summed to obtain motion information F(t) in frequency domain. In contrast, frequency based motion estimation approach lacks of localization problem [25]. Therefore, motions obtained in both spatial and frequency domains are combined with moving foreground objects for generating video summary.…”

Section: Motion Estimation In Frequency Domainmentioning

confidence: 99%

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Fusion of Foreground Object, Spatial and Frequency Domain Motion Information for Video Summarization

Salehin

Paul

2016

Image and Video Technology – PSIVT 2015 Workshops

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Surveillance video camera captures a large amount of continuous video stream every day. To analyze or investigate any significant events from the huge video data, it is laborious and boring job to identify these events. To solve this problem, a video summarization technique combining foreground objects as well as motion information in spatial and frequency domain is proposed in this paper. We extract foreground object using background modeling and motion information in spatial domain and frequency domain. Frame transition is applied for obtaining motion information in spatial domain. For acquiring motion information in frequency domain, phase correlation (PC) technique is applied. Later, foreground objects and motions in spatial and frequency domain are fused and key frames are extracted. Experimental results reveal that the proposed method performs better than the state-of-the-art method.

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Section: Motion Information Calculation In Spatial Domainmentioning

confidence: 99%

Section: Motion Estimation In Frequency Domainmentioning

confidence: 99%

Section: Motion Estimation In Frequency Domainmentioning

confidence: 99%

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