DynamicISP: Dynamically Controlled Image Signal Processor for Image Recognition
Masakazu Yoshimura, Junji Otsuka, Atsushi Irie, Takeshi Ohashi

TL;DR
DynamicISP adaptively adjusts image signal processing parameters in real-time based on recognition feedback, achieving high accuracy with low computational cost for image recognition tasks.
Contribution
We introduce DynamicISP, a novel method that dynamically controls ISP parameters per frame using recognition results, balancing expressive power and efficiency.
Findings
Achieves state-of-the-art accuracy in object detection
Maintains low computational cost on edge devices
Effectively controls multiple ISP functions dynamically
Abstract
Image Signal Processors (ISPs) play important roles in image recognition tasks as well as in the perceptual quality of captured images. In most cases, experts make a lot of effort to manually tune many parameters of ISPs, but the parameters are sub-optimal. In the literature, two types of techniques have been actively studied: a machine learning-based parameter tuning technique and a DNN-based ISP technique. The former is lightweight but lacks expressive power. The latter has expressive power, but the computational cost is too heavy on edge devices. To solve these problems, we propose "DynamicISP," which consists of multiple classical ISP functions and dynamically controls the parameters of each frame according to the recognition result of the previous frame. We show our method successfully controls the parameters of multiple ISP functions and achieves state-of-the-art accuracy with low…
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Videos
DynamicISP: Dynamically Controlled Image Signal Processor for Image Recognition· youtube
Taxonomy
TopicsAdvanced Memory and Neural Computing · Advanced Image and Video Retrieval Techniques · CCD and CMOS Imaging Sensors
