Decisões comportamentais em contexto de forrageamento de dinoponera quadriceps

The behavioral decisions of animals do not occur randomly, because behaviors are adjusted to ensure the survival and reproduction of the animal. In this research, I examined behavioral decisions in the foraging context of the ant Dinoponera quadriceps with regard to orientation, food avaliation and foraging dynamic to individual level. The study was conducted at the Laboratory of Behavioral Biology at UFRN and in an area of secondary Atlantic Forest in FLONA-ICMBio Nísia Floresta/RN. In all observations and experiments, ants were marked individually with an alphanumeric code label fixed on the thorax. In the first part of the study, I analyzed the orientation cues used by D. quadriceps. The tests were performed in a maze of 17 compartments. Each forager was tested for 10 min in three sessions for six different treatments. The treatments consisted of the presence or absence of odor and superior or frontal visual cues. The workers demonstrated that the presence of odor is indispensable and front visual cues are more effective than superior visual cues. In the second part, I investigated the discrimination of food, considering the parameters, size, weight and volume. In a 'cafeteria' experiment, I offered cylindrical pieces of food (mortadella) in a Petri dish, within an experimental arena 1m². Initially, the pieces were of four different sizes; in a second step, the pieces were of the same size but with different weight; in the last step, the pieces had the same weight but different volumes. The results showed the effect of the size and weight parameters for food choice. In the third part of the study, I evaluated the influence of the activity of active foragers on inactive ones. In this part, the colonies were observed in a natural environment. The observations took place on three consecutive days in 10 episodes, total of 30 days for each colony, 12 hours/day. On the first day, I registered the output and input of workers; on the second day, the most active ants on the first day were taken and given back at the end of the observations; on the third day, the observations were similar to the first day. As a result, the workers of D. quadriceps show autostimulation and they do not show social facilitation and the colony compensates the absence of the most active workers. Based on the stated, I conclude that workers of D. quadriceps use chemical, frontal and superior visual orientation cues during their displacements. They discriminate the chosen food by size and weight. The regulation of activity dynamics of foragers is by autostimulation, an active worker does not influence the activity of an inactive worker, the successful search previous is the stimulus to the successful worker itself to continue foraging activity.

An augmented reality pipeline to create scenes with coherent illumination using textured cuboids

Shadows and illumination play an important role when generating a realistic scene in computer graphics. Most of the Augmented Reality (AR) systems track markers placed in a real scene and retrieve their position and orientation to serve as a frame of reference for added computer generated content, thereby producing an augmented scene. Realistic depiction of augmented content with coherent visual cues is a desired goal in many AR applications. However, rendering an augmented scene with realistic illumination is a complex task. Many existent approaches rely on a non automated pre-processing phase to retrieve illumination parameters from the scene. Other techniques rely on specific markers that contain light probes to perform environment lighting estimation. This study aims at designing a method to create AR applications with coherent illumination and shadows, using a textured cuboid marker, that does not require a training phase to provide lighting information. Such marker may be easily found in common environments: most of product packaging satisfies such characteristics. Thus, we propose a way to estimate a directional light configuration using multiple texture tracking to render AR scenes in a realistic fashion. We also propose a novel feature descriptor that is used to perform multiple texture tracking. Our descriptor is an extension of the binary descriptor, named discrete descriptor, and outperforms current state-of-the-art methods in speed, while maintaining their accuracy.