Computer Vision is a field within data science and computer science that focuses on enabling machines to interpret and make decisions based on visual data. It involves the development of algorithms and models to extract meaningful information from images or videos, simulating the human ability to understand and interpret visual inputs. The primary goal of computer vision is to teach machines to recognize patterns, objects, and features in visual data.

Key tasks and applications in computer vision include:

1. Image Classification: Assigning a label or category to an entire image based on its content. For example, identifying whether an image contains a cat or a dog.
2. Object Detection: Locating and identifying multiple objects within an image, often by drawing bounding boxes around them. This is commonly used in applications like autonomous vehicles or surveillance systems.
3. Image Segmentation: Dividing an image into segments or regions based on certain criteria, such as colors or boundaries. It's useful for understanding the structure and content of an image.
4. Facial Recognition: Identifying and verifying individuals based on facial features. This is applied in security systems, authentication processes, and social media tagging.
5. Gesture Recognition: Recognizing and interpreting gestures or movements from images or video sequences, often used in human-computer interaction.
6. Object Tracking: Following the movement of objects over time in videos. This is essential for applications like video surveillance and sports analysis.
7. Scene Understanding: Inferring the overall context or meaning of a scene from visual input, including the relationships between objects and the interpretation of spatial arrangements.

Computer vision leverages various machine learning techniques, including deep learning, to automatically learn and extract features from visual data. Convolutional Neural Networks (CNNs) are particularly popular in computer vision tasks due to their ability to automatically learn hierarchical features from images.

The applications of computer vision are widespread and include industries such as healthcare, automotive, robotics, entertainment, and more. As technology advances, computer vision continues to play a crucial role in enhancing the capabilities of intelligent systems that can understand and interact with the visual world.