Processing video content at scale: Video data analysis as a reason to buy dedicated proxies
Contents of article:
- What is video data analysis?
- Why collect and analyze video data?
- What information can be obtained during video data analysis?
- How to perform video data analysis?
- Conclusion
The digital landscape has witnessed a surge in mobile information consumption. Applications for portable devices are common tools for communication, business, shopping, entertainment... Harvesting web data from mobile apps has become popular as well. We note therefore a rising demand on intermediate IPs for this purpose among users who buy residential and mobile proxies from the ethical Dexodata ecosystem.
Proliferation of video content is another trend. Video comprises 65 percent of global transmitted information and adds 30 percent more annually. TikTok, YouTube, Netflix, etc. provide terabytes of content suitable for business and scientific research. Gathering initial material and performing video data analytics requires buying dedicated proxies. This creates a basis for ethical and efficient internet info harvesting.
What is video data analysis?
Screen scraping involves the detection and management of visual and media elements on a chosen site. Video data analysis (VDA) is a more sophisticated procedure because of the initial source structure consisting of audio and graphical components. Video data analytics integrates:
- Inputting, when live-streamed or pre-recorded videos are inputted into the system, sourced from cameras or storage repositories.
- Processing, enabling AI-based computer vision and machine learning algorithms for detection, identification, and coding objects, actions, and real-time events.
- Valuable insights generation, when the results are conveyed to users through comprehensive reports and visualizations.
The video represents a consistent series of images, usually with 30 frames per second. The task is to detect and then categorize objects, their features and interactions, for further patterns’ determination. Considering a large amount of raw information, experts apply AI-driven advanced data analytics principles. The necessity to buy dedicated proxies is evident for acquiring publicly available insights during the initial phase.
Why collect and analyze video data?
VDA serves a multitude of purposes, including:
- Retail: to track in-store consumer behavior and traffic, measure queue length, and identify bottlenecks in the shopping experience.
- E-commerce: to extract valuable insights from videos, such as assessing ad effectiveness, detecting the virality of social media content.
- Smart cities: utilizing sensors and IoT devices to monitor traffic patterns, optimize urban planning and infrastructure, enhance public safety.
- Healthcare: to gather insights into patient care, disease management, and medical research.
- Manufacturing: to offer real-time insights into production processes, quality control, workplace safety, and resource utilization.
- Education and science: to enhance the learning experience by providing real-time feedback and personalized recommendations.
Performers should act in strict compliance with AML and KYC policies in the matters concerning personal information and individuals’ recognition. A similar principle is observed during ethical web scraping performed through residential and mobile proxies one buys from a proven source.
What information can be obtained during video data analysis?
There are two main types of obtained insights; structural and content. Their descriptions are presented below in tabular form.
| Data type | Structural features | Content features |
| Function | Encompassing the fundamental aspects of frame and video level | Delving into the essence of video content |
| Distinct characteristics | Primarily objective and technical | Visual elements and predictive insights turn into viewer perceptions |
| The necessity of AI-enhanced processing | No | Desirable |
| Elements for analysis |
|
|
Extracting content features mostly requires ML-based neural networks to classify various elements within the video. These could be faces, shapes, interior elements, advertising packshots. Furthermore, AI identifies and categorizes emotions, interactions, events, and anomalies. Among the applied solutions are:
- MTCNN, faces detection.
- YOLOv3, which gets selected objects in real-time.
- DeepLabCut or SLEAP to capture motions.
- ResNet-152, for spotting visual variance between two or more frames.
Advanced algorithms build casualties according to rules of training datasets. The same approach works for AI-driven web info extraction when raw metrics turn into structured schemes. To reduce dispersion and bias, scraping experts buy dedicated proxies from ethically maintained infrastructure. For video data analysis this means following AML and KYC policies while picking appropriate tools.
How to perform video data analysis?
Video data analysis starts by extracting suitable files using Java methods, MATLAB or Python. The VDA procedures necessitate high-performance hardware, typically a GPU with over 6 GB of memory. To perform video data analysis, one passes four phases:
- Selection of structural and content features for extraction.
- Coding video data. ML-based models label relevant content, including actors, objects, and spatial characteristics to work with.
- Analysis. Here, programs identify patterns, interpret them, and encompass aspects such as counts, timing, actors, and relationships.
- Processing labeled intelligence to draw conclusions or make predictions. Software tools for this purpose include OpenCV, IBM Watson Visual Recognition, and NVIDIA DeepStream. The ready-to-go insights are available for visualization and informed decision-making.
These stages form a framework for conducting effective video data analysis.
Conclusion
Video data analysis represents a sophisticated procedure for extracting insights from audio-visual content. Despite staying at the peak of technical progress, VDA faces several issues:
- Hardware performance for big data management
- Recognition of on-verbal interactions
- Ethical requirements for protecting filmed individuals or private information.
These complications are yet to be solved as opposed to ethical web scraping procedures. The credible Dexodata infrastructure offers to buy residential and mobile proxies and collect data for video analysis on an ethical basis.
