Methods for Object Orientation and Tracking

Dear Colleagues,

Popular artificial intelligence (AI) and machine learning (ML) image processing applications include object detection and classification. Large datasets with labeled objects are used to train models that are employed for the detection of specific objects in pictures of video frames. These datasets are augmented using techniques that rotate, crop, or distort the initial training images. This way, the training models are able to detect objects regardless of their orientation. However, there are certain applications where the orientation of the object of interest needs to be known. In road traffic or the monitoring of animals (e.g., fish), or in fruit harvesting, knowing the orientation of the vehicles, the fish, or the fruits, respectively, is necessary in order to perform the desired operations.

Object tracking, on the other hand, is a popular operation in many applications that include monitoring the movement of humans, animals, cars, or other objects. Object tracking and object orientation detection are often closely related. For example, the orientation of an object can be determined from its trajectory, and vice versa.

This Special Issue will showcase innovative papers related to “Methods for Object Orientation and Tracking”, including, but not limited to, the following topics:

• AI, ML, or image processing methods for object orientation classification;
• AI/ML methods for object tracking;
• Object tracking methods in human, livestock, or fish monitoring applications or for monitoring other objects, such as cars, planes, ships, or machinery;
• Object orientation classification methods in applications for monitoring cars, fish, plant leaves, and fruits;
• Neural network architectures appropriate for object tracking or orientation classification;
• Hardware acceleration techniques for object tracking and orientation classification;
• Real-time operation of object tracking and orientation techniques.

The aim of this Special Issue is to offer researchers working on object orientation classification an opportunity to present their achievements. The literature is quite poor in terms of object orientation classification approaches, and we invite researchers working on this topic to present their work in our dedicated Special Issue. New object tracking methods will also be presented, along with hardware platforms that support fast processing and real-time operation.

Dr. Nikos Petrellis
Guest Editor

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• object tracking
• orientation of objects
• real-time object tracking
• hardware-accelerated object tracking
• traffic management
• fish tracking
• fruit harvesting