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ABSTRACT: The use of image-based dietary assessment methods shows promise for improving dietary self-report among children. The Technology Assisted Dietary Assessment (TADA) food record application is a self-administered food record specifically designed to address the burden and human error associated with conventional methods of dietary assessment. Users would take images of foods and beverages at all eating occasions using a mobile telephone or mobile device with an integrated camera [e.g. Apple iPhone, Apple iPod Touch (Apple Inc., Cupertino, CA, USA); Nexus One (Google, Mountain View, CA, USA)]. Once the images are taken, the images are transferred to a back-end server for automated analysis. The first step in this process is image analysis (i.e. segmentation, feature extraction and classification), which allows for automated food identification. Portion size estimation is also automated via segmentation and geometric shape template modeling. The results of the automated food identification and volume estimation can be indexed with the Food and Nutrient Database for Dietary Studies to provide a detailed diet analysis for use in epidemiological or intervention studies. Data collected during controlled feeding studies in a camp-like setting have allowed for formative evaluation and validation of the TADA food record application. This review summarises the system design and the evidence-based development of image-based methods for dietary assessment among children.
Journal of Human Nutrition and Dietetics 03/2013; · 1.74 Impact Factor
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ABSTRACT: Poor diet is one of the key determinants of an
individual’s risk of developing chronic diseases. Assessing what
people eat is fundamental to establishing the link between diet
and disease. Food records are considered the best approach for
assessing energy intake however paper-based food recording is
cumbersome and often inaccurate. Researchers have begun to
explore how mobile devices can be used to reduce the burden
of recording nutritional intake. The integrated camera in a
mobile phone can be used for capturing images of food
consumed. These images are then processed to automatically
identify the food items for record keeping purposes. In such
systems, the accurate classification of food items in these
images is vital to the success of such a system. In this paper we
will present a new method for generating texture features from
food images and demonstrate that this new feature provides
greater food classification accuracy for a mobile phone based
dietary assessment system.
ICME 2012, Melbourne; 06/2012
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ABSTRACT: In recent years, there has been a growing interest in developing novel techniques for increasing the coding efficiency of video compression methods. One approach is to use texture and motion models of the content in a scene. Based on these models parts of the video frame are not coded or “skipped” by a classical motion compensated coder. The models are then used at the decoder to reconstruct the missing or skipped regions. In this paper, we describe several spatial-texture models for video coding. We investigate several texture features in combination with two segmentation strategies in order to detect texture regions in a video sequence. These detected areas are not encoded using motion compensated coding. The model parameters are sent to the decoder as side information. After the decoding process, frame reconstruction is done by inserting the skipped texture areas into the decoded frames. Using similar approach, we consider motion models based on human visual motion perception. We describe a motion classification model to separate foreground objects containing noticeable motion from the background. This motion model is then used in the encoder to again allow regions to be skipped and not coded using a motion compensated encoder. Our results indicate significant increase in terms of coding efficiency in comparison to the spatial texture-based methods. Finally, we discuss the effects and tradeoffs of these techniques based on perceptual experiments and show that in many cases the coding efficiency can be increased by up to 25% given a fixed perceptual quality.
IEEE Journal of Selected Topics in Signal Processing 12/2011; · 2.88 Impact Factor
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ABSTRACT: Digital image analysis is a fundamental component of quantitative microscopy. However, intravital microscopy presents many challenges for digital image analysis. In general, microscopy volumes are inherently anisotropic, suffer from decreasing contrast with tissue depth, lack object edge detail and characteristically have low signal levels. Intravital microscopy introduces the additional problem of motion artefacts, resulting from respiratory motion and heartbeat from specimens imaged in vivo. This paper describes an image registration technique for use with sequences of intravital microscopy images collected in time-series or in 3D volumes. Our registration method involves both rigid and nonrigid components. The rigid registration component corrects global image translations, whereas the nonrigid component manipulates a uniform grid of control points defined by B-splines. Each control point is optimized by minimizing a cost function consisting of two parts: a term to define image similarity, and a term to ensure deformation grid smoothness. Experimental results indicate that this approach is promising based on the analysis of several image volumes collected from the kidney, lung and salivary gland of living rodents.
Journal of Microscopy 11/2011; 245(2):148-60. · 1.63 Impact Factor
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ABSTRACT: Of the 10 leading causes of death in the US, 6 are related to diet. Unfortunately, methods for real-time assessment and proactive health management of diet do not currently exist. There are only minimally successful tools for historical analysis of diet and food consumption available. In this paper, we present an integrated database system that provides a unique perspective on how dietary assessment can be accomplished. We have designed three interconnected databases: an image database that contains data generated by food images, an experiments database that contains data related to nutritional studies and results from the image analysis, and finally an enhanced version of a nutritional database by including both nutritional and visual descriptions of each food. We believe that these databases provide tools to the healthcare community and can be used for data mining to extract diet patterns of individuals and/or entire social groups.
Multimedia and Expo (ICME), 2011 IEEE International Conference on; 08/2011
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ABSTRACT: In this paper we propose an image matching approach that selects the method of matching for each region in the image based on the region properties. This method can be used to find images similar to a query image from a database, which is useful for automatic image and video annotation. In this approach, each image is first divided into large homogeneous areas, identified as “texture areas”, and non-texture areas. Local descriptors are then used to match the keypoints in the non-texture areas, while texture regions are matched based on low level visual features. Experimental results prove that while exclusion of texture areas from local descriptor matching increases the efficiency of the whole process, utilization of appropriate measures for different regions can also increase the overall performance.
Content-Based Multimedia Indexing (CBMI), 2011 9th International Workshop on; 07/2011
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ABSTRACT: Local image features around interest-points have been widely used in order to exploit the similarities between different views of an object in different images. While there are numerous algorithms on detecting the interest-points and defining the local features, few have focused on the importance of the matching process. In this paper, we presented a method that matches interest-points detected via any algorithm. The method is motivated from human perceptual rules, particularly the Gestalt Psychology, and realizes the fact that “The whole is different from the sum of its parts”. The efficacy of the algorithm is not only the ability to decrease the number of false positive matches but also to increase the number of true positives, yielding rock-steady results for any algorithm based on matching local features.
Digital Signal Processing Workshop and IEEE Signal Processing Education Workshop (DSP/SPE), 2011 IEEE; 02/2011
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ABSTRACT: In this paper, we describe the Technology Assisted Dietary Assessment (TADA) project at Purdue University. Dietary intake, what someone eats during the course of a day, provides valuable insights for mounting intervention programs for prevention of many chronic diseases such as obesity and cancer. Accurate methods and tools to assess food and nutrient intake are essential for research on the association between diet and health. An overview of our methods used in the TADA project is presented. Our approach includes the use of image analysis tools for identification and quantification of food that is consumed at a meal. Images obtained before and after foods are eaten are used to estimate the amount and type of food consumed.
Multimedia (ISM), 2010 IEEE International Symposium on; 01/2011
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ABSTRACT: There is a growing concern about chronic diseases and other health problems related to diet including obesity and cancer. Dietary intake provides valuable insights for mounting intervention programs for prevention of chronic diseases. Measuring accurate dietary intake is considered to be an open research problem in the nutritions and health fields. In this paper, we describe a novel mobile telephone food record that provides a measure of daily food and nutrient intake. Our approach includes the use of image analysis tools for identification and quantification of food that is consumed at a meal. Images obtained before and after foods are eaten are used to estimate the amount and type of food consumed. The mobile device provides a unique vehicle for collecting dietary information that reduces the burden on respondents that are obtained using more classical approaches for dietary assessment. We describe our approach to image analysis that includes the segmentation of food items, features used to identify foods, a method for automatic portion estimation, and our overall system architecture for collecting the food intake information.
Image Processing (ICIP), 2010 17th IEEE International Conference on; 10/2010
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ABSTRACT: There is a growing concern about chronic diseases and other health problems related to diet including obesity and cancer. The need to accurately measure diet (what foods a person consumes) becomes imperative. Dietary intake provides valuable insights for mounting intervention programs for prevention of chronic diseases. Measuring accurate dietary intake is considered to be an open research problem in the nutrition and health fields. In this paper, we describe a novel mobile telephone food record that will provide an accurate account of daily food and nutrient intake. Our approach includes the use of image analysis tools for identification and quantification of food that is consumed at a meal. Images obtained before and after foods are eaten are used to estimate the amount and type of food consumed. The mobile device provides a unique vehicle for collecting dietary information that reduces the burden on respondents that are obtained using more classical approaches for dietary assessment. We describe our approach to image analysis that includes the segmentation of food items, features used to identify foods, a method for automatic portion estimation, and our overall system architecture for collecting the food intake information.
IEEE Journal of Selected Topics in Signal Processing 09/2010; · 2.88 Impact Factor
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ABSTRACT: We propose a low complexity method for segmentation of text regions in natural images. This algorithm is designed for mobile applications (e.g. unmanned or hand-held devices) in which computational and energy resources are limited. No prior assumption is made regarding the text size, font, language, character set or the camera angle. However, the text is assumed to be located on a piecewise homogeneous background with a contrasting color. We have deployed our method on a Nokia N800 Internet tablet as part of a system for automatic detection and translation of outdoor signs. Our experiments show that the 0.3 megapixel images taken by the phone camera can be accurately segmented within the device in a fraction of a second.
Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on; 04/2010 · 4.63 Impact Factor
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ABSTRACT: In this paper we propose a system for the analysis of user generated video (UGV). UGV often has a rich camera motion structure that is generated at the time the video is recorded by the person taking the video, i.e., the ??camera person.?? We exploit this structure by defining a new concept known as camera view for temporal segmentation of UGV. The segmentation provides a video summary with unique properties that is useful in applications such as video annotation. Camera motion is also a powerful feature for identification of keyframes and regions of interest (ROIs) since it is an indicator of the camera person's interests in the scene and can also attract the viewers' attention. We propose a new location-based saliency map which is generated based on camera motion parameters. This map is combined with other saliency maps generated using features such as color contrast, object motion and face detection to determine the ROIs. In order to evaluate our methods we conducted several user studies. A subjective evaluation indicated that our system produces results that is consistent with viewers' preferences. We also examined the effect of camera motion on human visual attention through an eye tracking experiment. The results showed a high dependency between the distribution of fixation points of the viewers and the direction of camera movement which is consistent with our location-based saliency map.
IEEE Transactions on Multimedia 02/2010; · 1.93 Impact Factor
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ABSTRACT: Recently there has been a great deal of interest using features intrinsic to a data-generating sensor for the purpose of source identification. Numerous methods have been proposed for different problems related to digital image forensics. The goal of our work is to identify the scanner used for generating a scanned (digital) version of a printed (hard-copy) document. In this paper we describe the use of texture analysis to identify the scanner used to scan a text document. The efficacy of our proposed method is also demonstrated.
Information Forensics and Security, 2009. WIFS 2009. First IEEE International Workshop on; 01/2010
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ABSTRACT: Optical microscopy exhibits many challenges for digital image analysis. In general, microscopy volumes are inherently anisotropic, suffer from decreasing contrast with tissue depth, and characteristically have low signal levels. This paper describes a method to segment multiphoton fluorescent microscopy images via a combination of segmentation and registration methods. In particular, the proposed method utilizes image enhancement and spatial filtering along with registration and temporal filtering. Experimental results demonstrate the efficacy of the proposed method.
Image Processing (ICIP), 2009 16th IEEE International Conference on; 12/2009
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ABSTRACT: Color space transformations are very common in digital imaging and display systems. Their complex mathematics requires hardware friendly implementations to make them practical. In this paper, look-up tables (LUT) are described for implementation of the color transformations. We show that this is possible because an analytical model of the transform is available for training and cross-validation. We identify parameters that affect the performance of a LUT-based system and then formulate the solution as an optimization problem.
Image Processing (ICIP), 2009 16th IEEE International Conference on; 12/2009
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ABSTRACT: We present a framework for developing a color transformation between two display devices to achieve a desired perceptual match. The framework is realized by first developing an optimal color transformation between the two devices, and then formulating an optimization problem to develop a hardware resource-constrained approximation to the optimal transformation. We employ the framework to investigate how well the system performs when the transformation is constrained to be a single 3Ã3 linear transformation directly between the non-linear RGB spaces of two devices. The motivation for this constraint is to ease resource requirements in a real-time hardware implementation.
Image Processing (ICIP), 2009 16th IEEE International Conference on; 12/2009
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ABSTRACT: One approach that can be used to increase compression efficiency beyond the data rates achievable by state-of-the-art video codecs is to use content-based methods whereby not all the pixels are conventionally encoded. An approach to reduce the data rate is to use different coding methods for pixels belonging to areas containing large amount of detail that are costly to encode, for example textures. This can be extended by focusing on the semantic meaning of objects represented in the video sequence and also taking into consideration human visual system properties. The goal is to determine where ¿detail-irrelevant¿ regions are located in the frame and synthesize them with acceptable perceptual quality. In this paper, we discuss the effects and trade-offs of these techniques based on a set of perceptual experiments and analyze how these areas can influence the viewer's attention.
Image Processing (ICIP), 2009 16th IEEE International Conference on; 12/2009
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ABSTRACT: In this paper we propose a system that annotates a user generated video based on the associated location metadata, by exploiting user-tagged image databases. An example of such a database is a photo sharing Web site such as Flickr where users upload their images and annotate them with various tags. The goal is to find the tags that have high probability of being relevant to the video without any complex object or action recognition being done to the video sequence. A video is first segmented into camera views and a set of keyframes are selected to represent the video. We will describe the concept of camera view as the basic element of user generated videos which has special properties suitable for the video annotation application. The keyframes are used to retrieve the most relevant images in the database. A ldquotag processingrdquo step is then used to tag the video.
Multimedia and Expo, 2009. ICME 2009. IEEE International Conference on; 08/2009
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ABSTRACT: In prior work, we proposed an unequal error protection algorithm based on Wyner-Ziv coding for error resilient video transmission. In subsequent work it was demonstrated that using either of content adaptive unequal error protection or feedback aided unequal error protection individually improved error resilience performance. In the current paper we propose to combine the use of a content adaptive function, implemented at the encoder, with the channel loss feedback provided by the decoder. The experimental results demonstrate improved rate distortion performance.
Picture Coding Symposium, 2009. PCS 2009; 06/2009
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ABSTRACT: In recent years there has been a growing interest in developing novel techniques for increasing the coding efficiency of video compression methods. We approach the problem by not encoding all the pixels, in particular, regions belonging to areas that the viewer will not perceive the specific details in the scene could be skipped or encoded at a much lower data rate. This approach can also be expanded by considering a model of the human visual perception system. In this paper we review some of the approaches we have investigated at Purdue University. The goal is to determine where ldquodetail-irrelevantrdquo regions in the frame are located and not encode them. We will also discuss a set of subjective quality evaluation experiments to determine what is the overall perceptual quality of these approaches.
Picture Coding Symposium, 2009. PCS 2009; 06/2009
