A Semi-Automated Technique for Transcribing Accurate Crowd Motions
| Autor: | Zhicheng Chen, Alexander Fuchsberger, Brian C. Ricks |
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| Rok vydání: | 2020 |
| Předmět: |
Novel technique
Computer science business.industry Pedestrian detection ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020207 software engineering 02 engineering and technology Automated technique Computer Graphics and Computer-Aided Design Motion capture Computer Science Applications Crowds Real-time simulation 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Computer Vision and Pattern Recognition Artificial intelligence business |
| Zdroj: | International Journal of Image and Graphics. 20:2050012 |
| ISSN: | 1793-6756 0219-4678 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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