Pascal VOC 2008 Challenge

To tackle the challenging dataset presented in this challenge, we use the highly successful appearance-based detector of Felzenszwalb et al. [1] and augment it with rich contextual cues extracted from the image to further improve its performance. Specifically, we train detectors to obtain the confidence that a window contains an object based solely on global scene statistics [2, 3], nearby regions, the object position and size, geographic context [4] and boundaries [5, 6]. Our interest is to study how much each of these contextual cues can add to the performance of the local appearance based detector. This report provides specific details of each of the individual cues used to tackle the classification, detection and segmentation competitions (more or less in a similar manner).