XCV is the research lab at the UC for applications of computer vision in the fields of (among others):
- X-ray Testing: recognition of prohibited objects in baggage inspection, detection of defects in castings and welds, characterization of food products (salmons, fruits, avocados, etc.) .
- Biometrics: face recognition in low quality images, facial attributes recognition (gender, expressions, etc.), iris recognition.
- Food Engineering: food characterization based on color analysis.
- Biology and Medicine: gait analysis of organisms based on video analytics and anomalies detection.
- Music: recognition of musical patterns using deep learning.
- Neuroscience: modeling search behaviors, analysis of MEG source reconstruction methods.
The focus of the XCV Research Lab is on 2D and 3D optical (conventional) and X-ray images that can be interpreted with the help of computer vision algorithms. Special interest of our lab is to create algorithms that can be used to aid human operators, and algorithms that can be used to learn new models based on human perception. We are trying to incorporate the richness of human visual perception in the core of the proposed computer vision algorithms.
In order to develop real-world applications of computer vision, the core of our research is the collaboration with local and international research labs and the industry.