ikkunatunnistus

Ikkunatunnistus, also known as window detection or eye tracking, is a computer vision technique used to identify and locate human eyes within an image or video stream. This process typically involves several stages. First, an image is preprocessed to enhance its quality and reduce noise. Then, algorithms are employed to detect potential eye regions, often by looking for circular or oval shapes with specific textural characteristics. Once potential eye candidates are found, further analysis is performed to confirm they are indeed eyes and to determine their precise location, size, and orientation. This can involve feature extraction, such as identifying pupils, irises, and eyelids.

The accuracy of ikkunatunnistus depends on various factors, including image resolution, lighting conditions, head pose, and the presence of occlusions like glasses or hair. Various algorithms exist for this task, ranging from traditional methods based on Haar cascades and SIFT features to more modern approaches utilizing deep learning models like Convolutional Neural Networks (CNNs).

Ikkunatunnistus has a wide range of applications. In human-computer interaction, it can be used for gaze-based control, allowing users to interact with devices using their eye movements. It is also employed in accessibility tools for individuals with motor impairments, in gaming for immersive experiences, and in research for understanding human behavior and attention. Furthermore, it plays a role in security systems for facial recognition and in driver monitoring systems to detect drowsiness or distraction.