Advances in Computer Vision & Image Processing: Image Enhancement, 3D Reconstruction, Motion Analysis, and Deep Learning-based Vision

Abstract

This paper reviews recent advances in computer vision and image processing, focusing on image enhancement, 3D reconstruction, motion analysis, and deep learning-driven systems. It explores classical and deep learning-based enhancement techniques in low-light, medical, and satellite imaging. 3D reconstruction methods, from stereo vision to deep learning, are assessed in applications like virtual reality and robotics. Motion analysis evaluates object detection and tracking under dynamic conditions. The impact of deep learning on object detection, segmentation, and recognition is emphasized, along with its integration into autonomous systems, intelligent transportation, and surveillance. Finally, challenges such as environmental robustness, computational constraints, and data scarcity are discussed, with future research directions outlined.