Two-in-one: Wide-angle monitoring meets high-resolution capture in new camera platform
Researchers construct a dual hybrid camera system enabling a 360-degree monitoring for target detection and its capture in high resolution
If you're a fan of spy movies, you've probably come across scenes where the intelligence agents try to identify or detect a perpetrator using some sophisticated image enhancement technology on surveillance camera images. While the idea behind surveillance cameras and object detection is the same in real life, unlike in movies, there is often a trade-off between the camera's field-of-view and its resolution.
Surveillance cameras are typically required to have a wide field-of-view to make the detection of a threat more likely. Due to this, omnidirectional cameras allowing a 360-degree capture range have become a popular choice, for the obvious reason that they leave out no blind spot but also because they're cheap to install. However, recent studies on object recognition in omnidirectional cameras show that distant objects captured in these cameras have rather poor resolution, making their identification difficult. While increasing the resolution is an obvious solution, the minimum resolution required, according to a study, is 4K (3840 X 2160 pixels), which translates to enormous bitrate requirements and a need for efficient image compression.
Moreover, 3D omnidirectional images often cannot be processed in raw form due to lens distortion effects and must be projected onto 2D first. "Continuous processing under high computational loads incurred by tasks such as moving object detection combined with converting a 360-degree video at 4K or higher resolutions into 2D images is simply infeasible in terms of real-life performance and installation costs," says Dr. Chinthaka Premachandra from Shibaura Institute of Technology (SIT), Japan, who researches image processing.
Addressing this issue in his latest END
Surveillance cameras are typically required to have a wide field-of-view to make the detection of a threat more likely. Due to this, omnidirectional cameras allowing a 360-degree capture range have become a popular choice, for the obvious reason that they leave out no blind spot but also because they're cheap to install. However, recent studies on object recognition in omnidirectional cameras show that distant objects captured in these cameras have rather poor resolution, making their identification difficult. While increasing the resolution is an obvious solution, the minimum resolution required, according to a study, is 4K (3840 X 2160 pixels), which translates to enormous bitrate requirements and a need for efficient image compression.
Moreover, 3D omnidirectional images often cannot be processed in raw form due to lens distortion effects and must be projected onto 2D first. "Continuous processing under high computational loads incurred by tasks such as moving object detection combined with converting a 360-degree video at 4K or higher resolutions into 2D images is simply infeasible in terms of real-life performance and installation costs," says Dr. Chinthaka Premachandra from Shibaura Institute of Technology (SIT), Japan, who researches image processing.
Addressing this issue in his latest END