Interactive Video Manipulation Using Object Trajectories and Scene Backgrounds

Shah, Rajvi; Narayanan, P. J.

doi:10.1109/tcsvt.2013.2248972

Cited by 16 publications

(6 citation statements)

References 33 publications

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“…Motion detection is a fundamental step in the lineage of information regarding objects in motion [26] and in simply counting the number of different pixels from the comparison between the reference image with the current one, for a fixed camera [20,21]. Therefore, more motion can be seen when there is a vast difference in pixels between two consecutive frames, and then we can sum up the absolute differences to get the Sum Average Difference (SAD).…”

Section: Motion Detectionmentioning

confidence: 99%

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Real-Time detection and tracking moving vehicles for video surveillance systems using FPGA

Fadhel¹,

Al-Shamaa²,

Taher³

2018

IJET

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With the growth of the electronic and communication devices, computer vision has become an significant application of smart cities. A smart city is controlled by smart autonomous systems. Many algorithms have been developed to satisfy these smart cities. This paper concerned with addressing the moving objects (vehicles) by using morphological techniques. For computational cheapness. The simulation has been built by a MATLAB 2012a and its implementation was done using Xilinx-ISE 14.6 (2013) XC3S700A-FPGA board that provides an exceptional tool for mixing between two platforms, the ISE 14.6(2013) and the MATLAB (2012a) platforms. MATLAB provides components for FPGA that invoke Verilog code of Xilinx platform, to avoid the size weakness of XC3S700A-FPGA board.

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Section: Motion Detectionmentioning

confidence: 99%

“…Then, the implementation of these comparisons has been represented as segmentation part in motion detection algorithm. Objects can be segmented out using the image subtraction technique for each pixel [26].…”

Section: Motion Detectionmentioning

confidence: 99%

Real-Time detection and tracking moving vehicles for video surveillance systems using FPGA

Fadhel¹,

Al-Shamaa²,

Taher³

2018

IJET

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“…Shah et al [24] focus on condensing large amounts of video into short animations but often result in disturbing artifacts such as ghosting. Users are given tools to cut and re-arrange trajectories in a spatio-temporal 3D volume in [19,30]. In DuctTake [26], events filmed in the same scene at different times are composed together using a graph-cut energy optimization, while Liao et al [18] build on this by allowing music to drive event re-ordering.…”

Section: Video Editingmentioning

confidence: 99%

“…Additionally, unlike in our approach, users must synchronize events manually to avoid incompatibilities, e.g. colliding cars [30]; outputs are limited to ones where filmed interactions are preserved [19], or they are not supported altogether [25].…”

Section: Video Editingmentioning

confidence: 99%

Responsive Action-based Video Synthesis

Ilisescu

Kanaci

Romagnoli

et al. 2017

Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

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We propose technology to enable a new medium of expression, where video elements can be looped, merged, and triggered, interactively. Like audio, video is easy to sample from the real world but hard to segment into clean reusable elements. Reusing a video clip means non-linear editing and compositing with novel footage. The new context dictates how carefully a clip must be prepared, so our end-to-end approach enables previewing and easy iteration. We convert static-camera videos into loopable sequences, synthesizing them in response to simple end-user requests. This is hard because a) users want essentially semantic-level control over the synthesized video content, and b) automatic loop-finding is brittle and leaves users limited opportunity to work through problems. We propose a human-in-the-loop system where adding effort gives the user progressively more creative control. Artists help us evaluate how our trigger interfaces can be used for authoring of videos and video-performances.Comment: 10 pages, 12 figures, 1 table, accepted and published in Proceedings of the 2017 CHI Conference on Human Factors in Computing System

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“…Traditional methods focus on extracting salient frames and displaying them in different forms, like video cubes in 3D [4], volume visualization for video sequences [5], keyframe posters [6], panorama excerpts [7], video booklets [8], video storyboarding frameworks [9], and so on. Other methods extract and visualize important information such as moving objects or movement trajectories [10,11]. These video summarization and visualization methods rarely consider the overall layout when integrating different scenes and interaction.…”

Section: Introductionmentioning

confidence: 99%

VideoMap: An interactive and scalable visualization for exploring video content

Guo

Wang

2016

Comp. Visual Media

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Large-scale dynamic relational data visualization has attracted considerable research attention recently. We introduce dynamic data visualization into the multimedia domain, and present an interactive and scalable system, VideoMap, for exploring large-scale video content. A long video or movie has much content; the associations between the content are complicated. VideoMap uses new visual representations to extract meaningful information from video content. Map-based visualization naturally and easily summarizes and reveals important features and events in video. Multi-scale descriptions are used to describe the layout and distribution of temporal information, spatial information, and associations between video content. Firstly, semantic associations are used in which map elements correspond to video contents.Secondly, video contents are visualized hierarchically from a large scale to a fine-detailed scale. VideoMap uses a small set of sketch gestures to invoke analysis, and automatically completes charts by synthesizing visual representations from the map and binding them to the underlying data. Furthermore, VideoMap allows users to use gestures to move and resize the view, as when using a map, facilitating interactive exploration. Our experimental evaluation of VideoMap demonstrates how the system can assist in exploring video content as well as significantly reducing browsing time when trying to understand and find events of interest.

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Interactive Video Manipulation Using Object Trajectories and Scene Backgrounds

Cited by 16 publications

References 33 publications

Real-Time detection and tracking moving vehicles for video surveillance systems using FPGA

Real-Time detection and tracking moving vehicles for video surveillance systems using FPGA

Responsive Action-based Video Synthesis

VideoMap: An interactive and scalable visualization for exploring video content

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