A Semi-Automated Technique for Transcribing Accurate Crowd Motions
International Journal of Image and Graphics, Vol: 20, Issue: 2
2020
- 99Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage99
- Downloads78
- Abstract Views21
Article Description
We present a novel technique for transcribing crowds in video scenes that allows extracting the positions of moving objects in video frames. The technique can be used as a more precise alternative to image processing methods, such as background-removal or automated pedestrian detection based on feature extraction and classification. By manually projecting pedestrian actors on a two-dimensional plane and translating screen coordinates to absolute real-world positions using the cross ratio, we provide highly accurate and complete results at the cost of increased processing time. We are able to completely avoid most errors found in other automated annotation techniques, resulting from sources such as noise, occlusion, shadows, view angle or the density of pedestrians. It is further possible to process scenes that are difficult or impossible to transcribe by automated image processing methods, such as low-contrast or low-light environments. We validate our model by comparing it to the results of both background-removal and feature extraction and classification in a variety of scenes.
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