Human-Centered Computer Vision

Contains fulltext : 241512.pdf (Publisher’s version ) (Open Access)Symposium on The Art and Science of Pattern Recognitio

Per què és bo perdonar?

TOTHOM S"HA SENTIT EMOCIONALMENT FERIT EN MÉS D"UNA OCASIÓ. Per un amic que ens ha decebut, per una acusació injusta... Davant d"aquestes emocions doloroses, sovint es reacciona amb irritació, hostilitat i desig de venjança. Després d"un temps de rancor, també hi ha qui decideix perdonar l"ofensorque no vol dir oblidar l"ofensa i renunciar al ressentiment. Hi ha persones molt més propenses que d"altres a gestionar els conflictes a través del perdó, i n"hi ha que se senten incapaces de fer-ho, la qual cosa les fa viure en un estat constant de còlera i d"emocions negatives que sovint requereix psicoteràpia, atès que l"angoixa que això els genera té importants conseqüències per a la salut. Pietro Petrini i els seus col·laboradors del Laboratori de Biologia Molecular i Bioquímica Clínica de la Universitat de Pisa (Itàlia) han publicat a Human Neuroscience el primer treball sobre la neuroanatomia funcional del perdó. Una de les principals conclusions és que la conseqüència final del perdó és retornar l"equilibri emocional i cognitiu a qui perdona

The utilization of human color categorization for content-based image retrieval

We present the concept of intelligent Content-Based Image Retrieval (iCBIR), which incorporates knowledge concerning human cognition in system development. The present research focuses on the utilization of color categories (or focal colors) for CBIR purposes, in particularly considered to be useful for query-by-heart purposes.However, this research explores its potential use for query-by-example purposes. Their use was validated for the field of CBIR by two experiments (26 subjects; stimuli: 4 times the 216 W3C web-safe colors) and one question ("mention ten colors"). Based on the experimental results a Color LookUp Table (CLUT) was defined. ThisCLUT was used to segment the HSI color space into the 11 color categories. With that a new color quantization method was introduced making a 11 bin color histogram configuration possible. This was compared with three other histogram configurations of 64, 166, and 4096 bins. Combined with the intersection and the quadratic distance measure we defined seven color matching systems. An experimentally founded benchmark for CBIR systems was implemented (1680 queries were performed measuring relevance and satisfaction). The 11 bin histogram configuration did have an average performance. A promising result since it was a naive implementation and is still a topic of development