Temporal Mapping of Surveillance Video

This work converts the surveillance video to a temporal domain image called temporal profile that is scrollable and scalable for quick searching of long surveillance video by human operators. Such a profile is sampled with linear pixel lines located at critical locations in the video frames. It has precise time stamp on the target passing events through those locations in the field of view, shows target shapes for identification, and facilitates the target search in long videos. In this paper, we first study the projection and shape properties of dynamic scenes in the temporal profile so as to set sampling lines. Then, we design methods to capture target motion and preserve target shapes for target recognition in the temporal profile. It also provides the uniformed resolution of large crowds passing through so that it is powerful in target counting and flow measuring. We also align multiple sampling lines to visualize the spatial information missed in a single line temporal profile. Finally, we achieve real time adaptive background removal and robust target extraction to ensure long-term surveillance. Compared to the original video or the shortened video, this temporal profile reduced data by one dimension while keeping the majority of information for further video investigation. As an intermediate indexing image, the profile image can be transmitted via network much faster than video for online video searching task by multiple operators. Because the temporal profile can abstract passing targets with efficient computation, an even more compact digest of the surveillance video can be created.

show abstract

“…Missing direction in a single temporal profile [29]. Enhanced by multi-temporal profiles with transparency [35].…”

Section: Resultsmentioning

confidence: 99%

Temporal mapping of surveillance video for indexing and summarization

Bagheri

Zheng

Sinha

2016

Computer Vision and Image Understanding

Self Cite

View full text Add to dashboard Cite

show abstract

“…In the following, the first part reviews the visual rhythm reorganization method first, adopted by ref. [4] and then proposes improvements based on the ref. [4] method to make it meet the research needs of this letter; the second part expounds on the influencing factors that lead to pedestrian deformation in the spatiotemporal domain and explains the relationship between each factor and the deformation of the spatiotemporal pedestrian.…”

Section: Related Technologiesmentioning

confidence: 99%

“…Reference [4] proposes a method to map a surveillance video to a temporal profile for indexing, and this method visualizes video contents effectively in a two‐dimensional (2D) temporal image and extracts a temporal profile from video to convey accurate temporal information. The method in ref.…”

Section: Introductionmentioning

confidence: 99%

“…The method in ref. [4] doesn't take the whole image as the processing unit but uses the visual rhythm to sample a part of the video frame and uses it as the processing unit to construct the temporal profile. This method has a small amount of calculation and strong representativeness [4].…”

Section: Introductionmentioning

confidence: 99%

“…[4] doesn't take the whole image as the processing unit but uses the visual rhythm to sample a part of the video frame and uses it as the processing unit to construct the temporal profile. This method has a small amount of calculation and strong representativeness [4]. However, in many cases, the temporal width of the pedestrian is squeezed due to the limited frame rate on close objects with fast speeds, resulting in the deformation of the pedestrian in the spatiotemporal domain, as shown in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive restoration of pedestrian appearance in the spatiotemporal domain

Zhang

Guo

Zhang

2021

The Journal of Engineering

View full text Add to dashboard Cite

Video synopsis based on visual rhythm has a small amount of calculation and strong representativeness, but the drawback is that the spatiotemporal pedestrians are distorted and illegible due to the loss of their own unique spatial morphology information, which leads to poor performance of video synopsis. To solve this problem, this letter proposed an adaptive restoration method of pedestrian appearance in the spatiotemporal domain. First, a single‐pixel row is taken as the sampling unit to complete the horizontal visual rhythm stitching; second, the relationship between the pedestrian spatiotemporal trajectory slope in the horizontal visual rhythm and the pedestrian movement speed is deduced; finally, the spatiotemporal trajectory slope is used as the basis for the vertical visual rhythm sampling width, and the adaptive restoration of pedestrian appearance in the spatiotemporal domain is completed. Experimental results show that the contour fluency and visual perception effect of pedestrian appearance restored by the proposed method are better, and the difference ratio of the proposed method is 0.08566, and the average running time is 421.0760 s, which has obvious advantages over the comparison method.

show abstract

Image Segmentation and Geometric Feature Based Approach for Fast Video Summarization of Surveillance Videos

Patel

Yadavannavar

et al. 2019

Communications in Computer and Information Science

View full text Add to dashboard Cite

Temporal Mapping of Surveillance Video

Cited by 4 publications

References 16 publications

Temporal mapping of surveillance video for indexing and summarization

Temporal mapping of surveillance video for indexing and summarization

Adaptive restoration of pedestrian appearance in the spatiotemporal domain

Image Segmentation and Geometric Feature Based Approach for Fast Video Summarization of Surveillance Videos

Contact Info

Product

Resources

About