- Computer Vision
- Emotion Evoked by Visual Data
- Image/Video Analysis
Incorporating Cloud Distribution in Sky Representation
Most sky models only describe the cloudiness or turbidity of the overall sky by single category or parameter such as sky index, which does not account for the distribution of the clouds across the sky. To capture this feature, we extend the concept of sky index to a random field indicating the level of cloudiness of each sky pixel in our proposed sky representation based on the Igawa sky model. We formulate the problem of solving the sky index of every sky pixel as a labeling problem, where an approximate solution can be efficiently found. Experimental results show that our proposed sky model has better expressiveness, stability with respect to variation in camera parameters, and geo-location estimation in outdoor images compared to the uniform sky index model. Potential applications of our proposed sky model include sky image rendering, where sky images can be generated with an arbitrary cloud distribution at any time and any location, previously impossible with traditional sky models.
Adding Emotions to Photos
Scene Segmentation Based on Normal Vectors