871 resultados para Machine vision and image processing
Resumo:
Deep convolutional network models have dominated recent work in human action recognition as well as image classification. However, these methods are often unduly influenced by the image background, learning and exploiting the presence of cues in typical computer vision datasets. For unbiased robotics applications, the degree of variation and novelty in action backgrounds is far greater than in computer vision datasets. To address this challenge, we propose an “action region proposal” method that, informed by optical flow, extracts image regions likely to contain actions for input into the network both during training and testing. In a range of experiments, we demonstrate that manually segmenting the background is not enough; but through active action region proposals during training and testing, state-of-the-art or better performance can be achieved on individual spatial and temporal video components. Finally, we show by focusing attention through action region proposals, we can further improve upon the existing state-of-the-art in spatio-temporally fused action recognition performance.
Resumo:
Milk microfiltration (0.05-0.2 um) is a membrane separation technique which divides milk components into casein-enriched and native whey fractions. Hitherto the effect of intensive microfiltration including a diafiltration step for both cheese and whey processing has not been studied. The microfiltration performance of skimmed milk was studied with polymeric and ceramic MF membranes. The changes caused by decreased concentration of milk lactose, whey protein and ash content for cheese milk quality and ripening were studied. The effects of cheese milk modification on the milk coagulation properties, cheese recovery yield, cheese composition, ripening and sensory quality as well as on the whey recovery yield and composition by microfiltration were studied. The functional properties of whey protein concentrate from native whey were studied and the detailed composition of whey protein concentrate powders made from cheese wheys after cheese milk pretreatments such as high temperature heat treatment (HH), microfiltration (MF) and ultrafiltration (UF) were compared. The studied polymeric spiral wound microfiltration membranes had 38.5% lower energy consumption, 30.1% higher retention of whey proteins to milk retentate and 81.9% lower permeate flux values compared to ceramic membranes. All studied microfiltration membranes were able to separate main whey proteins from skimmed milk. The optimal lactose content of Emmental cheese milk exceeded 3.2% and reduction of whey proteins and ash content of cheese milk with high concentration factor (CF) values increased the rate of cheese ripening. Reduction of whey protein content in cheese milk increased the concentration of caseinomacropeptide (CMP) of total proteins in cheese whey. Reduction of milk whey protein, lactose and ash content reduces milk rennet clotting time and increased the firmness of the coagulum. Cheese yield calculated from raw milk to cheese was lower with microfiltrated milks due to native whey production. Amounts of a-lactalbumin (a-LA) and b-lactoglobulin (b-LG) were significantly higher in the reference whey, indicating that HH, MF and UF milk pretreatments decrease the amounts of these valuable whey proteins in whey. Even low CF values in milk microfiltration (CF 1.4) reduced nutritional value of cheese whey. From the point of view of utilization of milk components it would be beneficial if the amount of native whey and the CMP content of cheese whey could be maximized. Whey protein concentrate powders made of native whey had excellent functional properties and their detailed amino acid composition differed from those of cheese whey protein concentrate powders.
Resumo:
In this paper we investigate the effectiveness of class specific sparse codes in the context of discriminative action classification. The bag-of-words representation is widely used in activity recognition to encode features, and although it yields state-of-the art performance with several feature descriptors it still suffers from large quantization errors and reduces the overall performance. Recently proposed sparse representation methods have been shown to effectively represent features as a linear combination of an over complete dictionary by minimizing the reconstruction error. In contrast to most of the sparse representation methods which focus on Sparse-Reconstruction based Classification (SRC), this paper focuses on a discriminative classification using a SVM by constructing class-specific sparse codes for motion and appearance separately. Experimental results demonstrates that separate motion and appearance specific sparse coefficients provide the most effective and discriminative representation for each class compared to a single class-specific sparse coefficients.
Resumo:
This paper presents a novel crop detection system applied to the challenging task of field sweet pepper (capsicum) detection. The field-grown sweet pepper crop presents several challenges for robotic systems such as the high degree of occlusion and the fact that the crop can have a similar colour to the background (green on green). To overcome these issues, we propose a two-stage system that performs per-pixel segmentation followed by region detection. The output of the segmentation is used to search for highly probable regions and declares these to be sweet pepper. We propose the novel use of the local binary pattern (LBP) to perform crop segmentation. This feature improves the accuracy of crop segmentation from an AUC of 0.10, for previously proposed features, to 0.56. Using the LBP feature as the basis for our two-stage algorithm, we are able to detect 69.2% of field grown sweet peppers in three sites. This is an impressive result given that the average detection accuracy of people viewing the same colour imagery is 66.8%.
Resumo:
In many parts of the world, uncontrolled fires in sparsely populated areas are a major concern as they can quickly grow into large and destructive conflagrations in short time spans. Detecting these fires has traditionally been a job for trained humans on the ground, or in the air. In many cases, these manned solutions are simply not able to survey the amount of area necessary to maintain sufficient vigilance and coverage. This paper investigates the use of unmanned aerial systems (UAS) for automated wildfire detection. The proposed system uses low-cost, consumer-grade electronics and sensors combined with various airframes to create a system suitable for automatic detection of wildfires. The system employs automatic image processing techniques to analyze captured images and autonomously detect fire-related features such as fire lines, burnt regions, and flammable material. This image recognition algorithm is designed to cope with environmental occlusions such as shadows, smoke and obstructions. Once the fire is identified and classified, it is used to initialize a spatial/temporal fire simulation. This simulation is based on occupancy maps whose fidelity can be varied to include stochastic elements, various types of vegetation, weather conditions, and unique terrain. The simulations can be used to predict the effects of optimized firefighting methods to prevent the future propagation of the fires and greatly reduce time to detection of wildfires, thereby greatly minimizing the ensuing damage. This paper also documents experimental flight tests using a SenseFly Swinglet UAS conducted in Brisbane, Australia as well as modifications for custom UAS.
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Scene understanding has been investigated from a mainly visual information point of view. Recently depth has been provided an extra wealth of information, allowing more geometric knowledge to fuse into scene understanding. Yet to form a holistic view, especially in robotic applications, one can create even more data by interacting with the world. In fact humans, when growing up, seem to heavily investigate the world around them by haptic exploration. We show an application of haptic exploration on a humanoid robot in cooperation with a learning method for object segmentation. The actions performed consecutively improve the segmentation of objects in the scene.
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This paper focuses on the time dimension in consumers’ image construction processes. Two new concepts are introduced to cover past consumer experiences about the company – image heritage, and the present image construction process - image-in-use. Image heritage and image-in-use captures the dynamic, relational, social, and contextual features of corporate image construction processes. Qualitative data from a retailing context were collected and analysed following a grounded theory approach. The study demonstrates that consumers’ corporate images have long roots in past experiences. Understanding consumers’ image heritage provides opportunities for understanding how consumers might interpret management initiatives and branding activities in the present.
Resumo:
The effect of neutralizing endogenous follicle stimulating hormone (FSH) or luteinizing hormone (LH) with specific antisera on the Image Image and Image Image synthesis of estrogen in the ovary of cycling hamster was studied. Neutralization of FSH or LH on proestrus resulted in a reduction in the estradiol concentration of the ovary on diestrus-2 and next proestrus, suggesting an impairment in follicular development.Injection of FSH antiserum at 0900 h of diestrus-2 significantly reduced the ovarian estradiol concentration within 6–7 h. Further, these ovaries on incubation with testosterone(T) Image Image at 1600 h of the same day or the next day synthesized significantly lower amounts of estradiol, compared to corresponding control ovaries. Although testosterone itself, in the absence of endogenous FSH, could stimulate estrogen synthesis to some extent, FSH had to be supplemented with T to restore estrogen synthesis to the level seen in control ovaries incubated with T. Lack of FSH thus appeared to affect the aromatization step in the estrogen biosynthetic pathway in the ovary of hamster on diestrus-2. In contrast to this, FSH antiserum given on the morning of proestrus had no effect on the Image Image and Image Image synthesis of estrogen, when examined 6–7 h later. The results suggest that there could be a difference in the need for FSH at different times of the cycle.Neutralization of LH either on diestrus-2 or proestrus resulted in a drastic reduction in estradiol concentration of the ovary. This block was at the level of androgen synthesis, since supplementing testosterone alone Image Image could stimulate estrogen synthesis to a more or less similar extent as in the ovaries of control hamsters.
Resumo:
Asperger Syndrome (AS) belongs to autism spectrum disorders where both verbal and non-verbal communication difficulties are at the core of the impairment. Social communication requires a complex use of affective, linguistic-cognitive and perceptual processes. In the four studies included in the current thesis, some of the linguistic and perceptual factors that are important for face-to-face communication were studied using behavioural methods. In all four studies the results obtained from individuals with AS were compared with typically developed age, gender and IQ matched controls. First, the language skills of school-aged children were characterized in detail with standardized tests that measured different aspects of receptive and expressive language (Study I). The children with AS were found to be worse than the controls in following complex verbal instructions. Next, the visual perception of facial expressions of emotion with varying degrees of visual detail was examined (Study II). Adults with AS were found to have impaired recognition of facial expressions on the basis of very low spatial frequencies which are important for processing global information. Following that, multisensory perception was investigated by looking at audiovisual speech perception (Studies III and IV). Adults with AS were found to perceive audiovisual speech qualitatively differently from typically developed adults, although both groups were equally accurate in recognizing auditory and visual speech presented alone. Finally, the effect of attention on audiovisual speech perception was studied by registering eye gaze behaviour (Study III) and by studying the voluntary control of visual attention (Study IV). The groups did not differ in eye gaze behaviour or in the voluntary control of visual attention. The results of the study series demonstrate that many factors underpinning face-to-face social communication are atypical in AS. In contrast with previous assumptions about intact language abilities, the current results show that children with AS have difficulties in understanding complex verbal instructions. Furthermore, the study makes clear that deviations in the perception of global features in faces expressing emotions as well as in the multisensory perception of speech are likely to harm face-to-face social communication.
Resumo:
We present an algorithm for tracking objects in a video sequence, based on a novel approach for motion detection. We do not estimate the velocity �eld. In-stead we detect only the direction of motion at edge points and thus isolate sets of points which are moving coherently. We use a Hausdor� distance based matching algorithm to match point sets in local neighborhood and thus track objects in a video sequence. We show through some examples the e�ectiveness of the algo- rithm.