Speedy Object Detection based on Shape
This work addresses the need for efficient object detection in assistive technology for visually impaired people, but it appears incremental as it builds on existing shape-based methods without specifying major breakthroughs.
The study tackled the problem of real-time object detection for an audio-based assistive system for visually impaired individuals by proposing a shape-based detection method that reduces computational operations, achieving faster detection speeds.
This study is a part of design of an audio system for in-house object detection system for visually impaired, low vision personnel by birth or by an accident or due to old age. The input of the system will be scene and output as audio. Alert facility is provided based on severity levels of the objects (snake, broke glass etc) and also during difficulties. The study proposed techniques to provide speedy detection of objects based on shapes and its scale. Features are extraction to have minimum spaces using dynamic scaling. From a scene, clusters of objects are formed based on the scale and shape. Searching is performed among the clusters initially based on the shape, scale, mean cluster value and index of object(s). The minimum operation to detect the possible shape of the object is performed. In case the object does not have a likely matching shape, scale etc, then the several operations required for an object detection will not perform; instead, it will declared as a new object. In such way, this study finds a speedy way of detecting objects.