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Understanding machine vision can certainly improve our understanding of artificial intelligence as vision happens to be one of the basic intellectual activities of living beings. Since the notion of computation unifies the concept of a machine, computer vision can be understood as an application of modern approaches for achieving artificial intelligence, like machine learning and cognitive psychology. Computer vision mainly involves processing of different types of sensor data resulting in "perception of machines". Perception of machines plays a very important role in several artificial intelligence applications with sensors. There are numerous practical situations where we acquire sensor data for e.g. from mobile robots, security cameras, service and recreational robots. Making sense of this sensor data is very important so that we have increased automation in using the data. Tools from image processing, shape analysis and probabilistic inferences i.e. learning theory form the artillery for current generation of computer vision researchers. In my thesis I will address some of the most annoying components of two important open problems viz. object recognition and autonomous navigation that remain central in robotic, or in other words computational, intelligence. These problems are concerned with inducing computers, the abilities to recognize and navigate similar to those of humans. Object boundaries are very useful descriptors for recognizing objects. Extracting boundaries from real images has been a notoriously open problem for several decades in the vision community. In the first part I will present novel techniques for extracting object boundaries. The techniques are based on practically successful state-of-the-art Bayesian filtering framework, well founded geometric properties relating boundaries and skeletons and robust high-level shape analyses Acquiring global maps of the environments is crucial for robots to localize and be able to navigate autonomously. Though there has been a lot of progress in achieving autonomous mobility, for e.g. as in DARPA grand-challenges of 2005 and 2007, the mapping problem itself remains to be unsolved which is essential for robust autonomy in hard cases like rescue arenas and collaborative exploration. In the second part I will present techniques for merging maps acquired by multiple and single robots. We developed physics-based energy minimization techniques and also shape based techniques for scalable merging of maps. Our shape based techniques are a product of combining of high-level vision techniques that exploit similarities among maps and strong statistical methods that can handle uncertainties in Bayesian sense. / Computer and Information Science

Leopard frogs (Rana pipiens) rely on vision to recognize behaviorally meaningful aspects of their environment. The optic tectum has been shown to mediate the frog's ability to recognize and respond to moving prey and looming objects. Nonetheless, atectal frogs are still able to appropriately respond to non-moving aspects of their environment. There appears to be independent visual systems operating in the frog: one system for recognizing moving objects; and another system for recognizing stationary objects. Little is known about the neural mechanisms mediating the recognition of stationary objects in frogs. Our laboratory showed that a retino-recipient area in the anterior lateral thalamus--the NB/CG zone--is involved in processing visual information concerning stationary aspects of the environment. This thesis aims to characterize the frog's responses to a range of stationary stimuli, and to elucidate the thalamic visual system that mediates those responses. I tested leopard frogs' responses to different stationary stimuli and found they respond in stereotypical ways. I discovered that leopard frogs are attracted to dark, stationary, opaque objects; and tested the extent of this attraction under different conditions. I found that frogs' preference to move toward a dark area versus a light source depends on the intensity of the light source relative to the intensity of ambient light. Unilateral lesions applied to the NB/CG zone of the anterior lateral thalamus resulted in temporary deficits in frogs' responses to stationary stimuli presented in the contralateral visual field. Deficits were observed in response to: dark objects, entrances to dark areas, light sources, and gaps between stationary barriers. However, responses to moving prey and looming stimuli were unaffected. Interestingly, these deficits tended to recover after about 6 days in most cases. Recovery time ranged from 2 - 28 days. The NB/CG zone is anatomically and functionally connected to a structure in the posterior thalamus called the "PMDT." The PMDT has no other connections in the brain. Thus, I have discovered a "satellite" of the NB/CG zone. Preliminary evidence suggests that the PMDT is another component of the visual system mediating stationary object recognition in the frog. / Biology

Object recognition systems require baseline information upon which to compare sensed data to enable a recognition task. The ability to integrate a diverse set of object recognition data for different components in a Building Information Model (BIM) will enable many autonomous systems to access and use these data in an on-demand learning capacity, and will accelerate the integration of object recognition systems in the construction environment. This research presents a new framework for linking feature descriptors to a BIM to support construction object recognition. The proposed framework is based upon the Property and External Reference Resource schemas within the IFC 2x3 TC1 architecture. Within this framework a new Property Set (Pset_ObjectRecognition) is suggested which provides an on-demand capability to access available feature descriptor information either embedded in the IFC model or referenced in an external model database. The Property Set is extensible, and can be modified and adjusted as required for future research and field implementation. With this framework multiple sets of feature descriptors associated with different sensing modalities and different algorithms can all be aggregated into one Property Set and assigned to either object types or object instances. / Ph. D.

Yes / Cholinergic dysfunction has been shown to be central to the pathophysiology of Alzheimer’s disease and has also been postulated to contribute to cognitive dysfunction observed in various psychiatric disorders, including schizophrenia. Deficits are found across a number of cognitive domains and in spite of several attempts to develop new therapies, these remain an unmet clinical need. In the current study we investigated the efficacy of donepezil, risperidone and selective nicotinic α7 and α4β2 receptor agonists to reverse a delay-induced deficit in recognition memory. Adult female Hooded Lister rats received drug treatments and were tested in the novel object recognition (NOR) task following a 6 h inter-trial interval (ITI). In all treatment groups, there was no preference for the left or right identical objects in the acquisition trial. Risperidone failed to enhance recognition memory in this paradigm whereas donepezil was effective such that rats discriminated between the novel and familiar object in the retention trial following a 6 h ITI. Although a narrow dose range of PNU-282987 and RJR- 2403 was tested, only one dose of each increased recognition memory, the highest dose of PNU-282987 (10 mg/kg) and the lowest dose of RJR-2403 (0.1 mg/kg), indicative of enhanced cognitive performance. Interestingly, these compounds were also efficacious when administered either before the acquisition or the retention trial of the task, suggesting an important role for nicotinic receptor subtypes in the formation and retrieval of recognition memory. / This work was conducted at the University of Bradford and was funded by b-neuro. However all our recent studies mentioned in the discussion section have been conducted at the University of Manchester (UoM), and funded by b-neuro, Autifony, Innovate UK (formerly TSB) and UoM

Yes / In many species, seasonal changes in day length (photoperiod) have profound effects on physiology and behavior. In humans, these include cognitive function and mood. Here we investigated the effect of photoperiod and high fat diets on cognitive deficits, as measured by novel object recognition, in the photoperiod-sensitive F344 rat, which exhibits marked natural changes in growth, body weight and food intake in response to photoperiod. 32 male juvenile F344 rats were housed in either long or short photoperiod and fed either a high fat or nutrient-matched chow diet. Rats were tested in the novel object recognition test before photoperiod and diet intervention and re-tested 28 days after intervention. In both tests during the acquisition trials there was no significant difference in exploration levels of the left and right objects in the groups. Before intervention, all groups showed a significant increase in exploration of the novel object compared to the familiar object. However, following the photoperiod and diet interventions the retention trial revealed that only rats in the long photoperiod-chow group explored the novel object significantly more than the familiar object, whereas all other groups showed no significant preference. These results suggest that changing rats to short photoperiod impairs their memory regardless of diet. The cognitive performance of rats on long photoperiod-chow remained intact, whereas the high fat diet in the long photoperiod group induced a memory impairment. These findings suggest that rats exposed to long photoperiod have different cognitive responses to rats exposed to short photoperiod and high fat diet.

Yes / Rationale: Nicotinic α7 acetylcholine receptors (nAChRs) have been highlighted as a target for cognitive enhancement in schizophrenia. Aim: To investigate whether the deficits induced by sub-chronic phencyclidine (PCP) in reversal learning and novel object recognition could be attenuated by the selective α7 nAChR full agonist, PNU-282987. Methods: Adult female hooded-Lister rats received sub-chronic PCP (2 mg/kg) or vehicle i.p. twice daily for seven days, followed by 7-days washout. In cohort 1, PCP-treated rats then received PNU-282987 (5, 10, 20 mg/kg; s.c.) or vehicle and were tested in the reversal learning task. In cohort 2, PCP-treated rats received PNU-282987 (10 mg/kg; s.c.) or saline for 15 days and were tested in the novel object recognition test on day 1 and on day 15, to test for tolerance. Results: Sub-chronic PCP produced significant deficits in both cognitive tasks (P<0.01-0.001). PNU-282987 attenuated the PCP-induced deficits in reversal learning at 10 mg/kg (P<0.01) and 20 mg/kg (P<0.001), and in novel object recognition at 10 mg/kg on day 1 (P<0.01) and on day 15 (P<0.001). Conclusions: These data show that PNU-282987 has efficacy to reverse PCP-induced deficits in two paradigms of relevance to schizophrenia. Results further suggest that 15 day daily dosing of PNU-282987 (10 mg/kg s.c.) does not cause tolerance in rat. This study suggests that activation of α7 nAChRs, may represent a suitable strategy for improving cognitive deficits of relevance to schizophrenia. / SL McLean was supported by a joint University of Bradford–GSK postgraduate studentship.

This thesis describes an approach for object recognition using the chordiogram shape-based descriptor. Global shape representations are highly susceptible to clutter generated due to the background or other irrelevant objects in real-world images. To overcome the problem, we aim to extract precise object shape using superpixel segmentation, perceptual grouping, and connected components. The employed shape descriptor chordiogram is based on geometric relationships of chords generated from the pairs of boundary points of an object. The chordiogram descriptor applies holistic properties of the shape and also proven suitable for object detection and digit recognition mechanisms. Additionally, it is translation invariant and robust to shape deformations. In spite of such excellent properties, chordiogram is not scale-invariant. To this end, we propose scale invariant chordiogram descriptors and intend to achieve a similar performance before and after applying scale invariance. Our experiments show that we achieve similar performance with and without scale invariance for silhouettes and real world object images. We also show experiments at different scales to confirm that we obtain scale invariance for chordiogram.