Five Core Tasks of Computer Vision

Computer vision is not only a science that studies how to make machines understand and interpret the visual world, but also a technology that aims to enable machines to have visual processing capabilities similar to humans.

By analyzing digital images and videos, machines can recognize, track, and understand objects and scenes in the real world.

Image classification is the task of assigning an image to a specific category, while image recognition further associates the category with specific entities or objects. For example, the classification task may identify whether a cat is present in the image, while the recognition task distinguishes between different types of cats, from domestic cats to wild leopards.

Image classification and recognition, as the cornerstone of computer vision, perfectly reflect the rapid progress of the entire field. From manually designed features to complex deep learning models, this field not only showcases the powerful capabilities of computer vision but also lays a solid foundation for future innovations and developments.

With the advancement of more sophisticated algorithms and hardware, we look forward to image classification and recognition playing a role in more scenarios to meet the growing demands of people.

Object detection not only requires identifying objects in an image but also accurately determining their location and category. Its applications include facial recognition, traffic analysis, and product quality inspection. The object segmentation task is even more detailed, involving pixel-level object analysis.

Object detection and segmentation combine multiple aspects of image processing, machine learning, and deep learning, making it a complex and multifaceted task in computer vision. Its wide applications span autonomous driving, medical diagnostics, and intelligent monitoring. Future research will focus more on cutting-edge challenges such as multimodal information fusion, few-shot learning, and real-time high-precision detection, continuously driving innovation and development in this field.

Human analysis is an important and active research area in computer vision, covering tasks such as recognition, detection, segmentation, pose estimation, and action recognition of the human body.

The research and application of human analysis have far-reaching impacts in many fields, including security monitoring, healthcare, entertainment, and virtual reality.

3D computer vision is a field full of challenges and opportunities. From basic 3D reconstruction to complex 3D object recognition and semantic segmentation, research in this area has had a profound impact on many advanced technologies and applications.

With the continuous advancement of hardware and algorithms, 3D computer vision will continue to drive the development of many cutting-edge technologies, such as autonomous driving, smart city construction, and virtual and augmented reality. In the future, we can expect more innovations and breakthroughs in this field.

Video understanding and analysis is an important branch of computer vision, involving not only the recognition and interpretation of video content but also the reasoning of temporal and spatial structures.

Compared to single image analysis, video analysis can delve deeper into the continuity and intrinsic connections of visual information, thus opening up new fields in computer vision.