Models of object recognition in cortex have so far been mostly applied to tasks involving the recognition of isolated objects presented on blank backgrounds. However, ultimately models of the visual system have to prove themselves in real world object recognition tasks. Here we took a first step in this direction: We investigated the performance of the hmax model of object recognition in cortex...

Different from many gesture-based human-robot interaction applications, which focused on the recognition of the interactional or the pointing gestures, this paper proposes a vision-based method for manipulative gesture recognition aiming to achieve natural, proactive, and non-intrusive interaction between humans and robots. The main contributions of the paper are an object-centered scheme for t...

Sleep has been shown to play a facilitating role in memory consolidation, whereas sleep deprivation leads to performance impairment both in humans and rodents. The effects of 4-h sleep deprivation on recognition memory were investigated in the Djungarian hamster (Phodopus sungorus). Because sleep during the first hours after daily torpor has many similarities to recovery from sleep deprivation,...

Most artiicial intelligence systems today work on simple problems and artiicial domains because they rely on the accurate sensing of the task world. Object recognition is a crucial part of the sensing challenge and machine learning stands in a position to catapult object recognition into real world domains. Given that, to date, machine learning has not delivered general object recognition, we p...

Most artiicial intelligence systems today work on simple problems and artiicial domains because they rely on the accurate sensing of the task world. Object recognition is a crucial part of the sensing challenge and machine learning stands in a position to catapult object recognition into real world domains. Given that, to date, machine learning has not delivered general object recognition, we p...

The problem of recognizing generic object categories is one of most active areas in computer vision and pattern recognition. The problem lies in the center of visual object recognition challenge. The task is trying to automatically recognition genetic object in natural scene. The problem statement: It views whole image as one item, aim at extracting the most impressive Region of Interests (ROI)...

Object Recognition is an important task in many Computer Vision problems. The problem is usually defined as classifying new images given a set of training images. One of the most challenging problems is Category-level Object Recognition which has got attention in the past decade. In this project the work on Fine-grained Category Object Recognition is presented. Despite General Object Recognitio...

In the model room task, children watch as a miniature toy is hidden somewhere in a scale model of a room and are asked to find the larger version of the toy in the corresponding place in the actual room. Previous work has shown that children under age three often perform very poorly on this task. One prominent theory for their failure is that they lack the ability to understand the model as bot...

Visual recognition is a fundamental yet challenging computer vision task. In the recent years there have been tremendous interest in investigating the use of local features and parts in generic object recognition-related problems such as, object categorization, localization, discovering object categories, recognizing objects from different views, etc. In this Chapter we present a framework for ...

Individual differences in face recognition are often contrasted with differences in object recognition using a single object category. Likewise, individual differences in perceptual expertise for a given object domain have typically been measured relative to only a single category baseline. In Experiment 1, we present a new test of object recognition, the Vanderbilt Expertise Test (VET), which ...