《人像摄影》课程多专业联合创作创新研究

《人像摄影》课程是一门典型的高校摄影专业必修课程,学生对此课程的掌握程度直接地影响了学生的创作能力以及就业前景。本论文通过对北京城市学院摄影专业的《人像摄影》课程创新研究,结合北京城市学院本身具备的专业便利条件,尝试与表演(服装表演)专业、人物造型设计专业进行跨专业合作授课,让三个专业的学生在课堂中体验摄影行业合作模式,尝试提出与时代需求更加契合的教学思路,对以往授课过程中的不足提出新的解决办法,并通过实际授课过程来观察实践效果,最后对此创新授课方式得到的效果进行分析。

Monitoring coal fires in Datong coalfield using multi-source remote sensing data

Numerous coal fires burn underneath the Datong coalfield because of indiscriminate mining.Landsat TM/ETM,unmanned aerial vehicle（UAV）,and infrared thermal imager were employed to monitor underground coal fires in the Majiliang mining area.The thermal field distributions of this area in 2000,2002,2006,2007,and 2009 were obtained using Landsat TM/ETM.The changes in the distribution were then analyzed to approximate the locations of the coal fires.Through UAV imagery employed at a very high resolution（0.2 m）,the texture information,linear features,and brightness of the ground fissures in the coal fire area were determined.All these data were combined to build a knowledge model of determining fissures and were used to support underground coal fire detection.An infrared thermal imager was used to map the thermal field distribution of areas where coal fire is serious.Results were analyzed to identify the hot spot trend and the depth of the burning point.

Face hallucination via compressive sensing

Face hallucination or super-resolution is an inverse problem which is underdetermined,and the compressive sensing(CS)theory provides an effective way of seeking inverse problem solutions.In this paper,a novel compressive sensing based face hallucination method is presented,which is comprised of three steps:dictionary learning、sparse coding and solving maximum a posteriori(MAP)formulation.In the first step,the K-SVD dictionary learning algorithm is adopted to obtain a dictionary which can sparsely represent high resolution(HR)face image patches.In the second step,we seek the sparsest representation for each low-resolution(LR)face image paches input using the learned dictionary,super resolution image blocks are obtained from the sparsest coefficients and dictionaries,which then are assembled into super-resolution(SR)image.Finally,MAP formulation is introduced to satisfy the consistency restrictive condition and obtain the higher quality HR images.The experimental results demonstrate that our approach can achieve better super-resolution faces compared with other state-of-the-art method.

兰莉画廊

兰莉画廊位于上海市徐家汇商业中心、徐家汇天主教堂房,环境优雅,充满浓郁的文化艺术氛围。画廊展出面积近200平方米,定期展示国内外著名艺术家作品,举办各类画展,同时不断推出富有潜力和前景的新人制作。 兰莉画廊经营展示的作品,注重艺术质量、品位、水准,在艺术家和收藏家之间进行广泛的联系,在专业人士的管理下,向收藏者负责。

Change Detection Based on DSM and Image Features in Urban Areas

On the basis of stereo image analysis, the change detection of man-made objects in urban areas is introduced. Information of the height of man-made objects can be applied to reinforce their change detection. By comparison between the new and old DSMs, the changed regions are extracted. However, our aim is to detect changes of man-made objects in urban area and further in the potential areas by the means of line-feature matching and gradient direction histogram. The experiments based on the aerial images from Japan have proven that the algorithm is correct and efficient.

SOME KEY ISSUES ON THE APPLICATION OF SATELLITE REMOTE SENSING TO MINING AREAS

In order to apply Satellite Remote Sensing (RS) to mining areas, some key issues should be solved. Based on an introduction to relative studying background, related key issues are proposed and analyzed oriented to the development of RS information science and demands of mining areas. Band selection and combination optimization of Landsat TM is discussed firstly, and it proved that the combination of Band 3, Band 4 and Band 5 has the largest information amount in all three-band combination schemes by both N-dimensional entropy method and Genetic Algorithm (GA). After that the filtering of Radarsat image is discussed. Different filtering methods are experimented and compared, and adaptive methods are more efficient than others. Finally the classification of satellite RS image is studied, and some new methods including classification by improved BPNN(Back Propagation Neural Network) and classification based on GIS and knowledge are proposed.

Eagle-Vision-Based Object Detection Method for UAV Formation in Hazy Weather

Inspired by eagle’s visual system,an eagle-vision-based object detection method for unmanned aerial vehicle(UAV)formation in hazy weather is proposed in this paper.To restore the hazy image,the values of atmospheric light and transmission are estimated on the basis of the signal processing mechanism of ON and OFF channels in eagle’s retina.Local features of the dehazed image are calculated according to the color antagonism mechanism and contrast sensitivity function of eagle’s visual system.A center-surround operation is performed to simulate the response of reception field.The final saliency map is generated by the Random Forest algorithm.Experimental results verify that the proposed method is capable to detect UAVs in hazy image and has superior performance over traditional methods.

Giant hepatobiliary cystadenoma in a male with obvious convex papillate

Hepatobiliary cystadenoma that is most often found in is an uncommon lesion middle-aged women and difficult to diagnose preoperatively. Here, we report a case of giant hepatobiliary cystadenoma in a male patient with obvious convex papillate. On the basis of imaging examinations, the patient was diagnosed as hepatobiliary cystadenoma prior to operation. Left hepatectomy was performed and the patient was symptom-free during a 6-too follow-up period, suggesting that imaging examination is the major diagnostic method of hepatobiliary cystadenoma, and operation is its best treatment modality.

Small bowel MRI enteroclysis or follow through:Which is optimal?

AIM： TO determine if a nasojejunal tube （NJT） is required for optimal examination of enteroclysis and if patients can be examined only in the supine position. METHODS： Data were collected from all patients undergoing small bowel （SB） magnetic resonance imaging （MRI） examination over a 32-mo period. Patients either underwent a magnetic resonance （MR） follow-through （MRFT） or a MR enteroclysis （MRE） in the supine position. The quality of proximal and distal SB distension as well as the presence of motion artefact and image quality were assessed by 2 radiologists. RESULTS： One hundred and fourteen MR studies were undertaken （MRFT-49, MRE-65） in 108 patients in the supine position only. Image artefact was more frequent in MRE than in MRFT （29.2% vs 18.4%）, but was not statistically significant （P = 0.30）. Adequate distension of the distal SB was obtained in 97.8% of MRFT examinations and in 95.4% of MRE examinations, respectively. Proximal SB distension was, however, less frequently optimal in MRFT than in MRE （P = 0.0036）, particularly in patients over the age of 50 years （P = 0.0099）. Image quality was good in all examinations. CONCLUSION： All patients could be successfully iraaged in the supine position. MRE and MRFT are equivalent for distal SB distension and artefact effects. Proximal SB distension is frequently less optimal in MRFT than in MRE. MRE is, therefore, the preferred MR examination method of the SB.

Cultivated land information extraction in UAV imagery based on deep convolutional neural network and transfer learning

The development of precision agriculture demands high accuracy and efficiency of cultivated land information extraction. As a new means of monitoring the ground in recent years, unmanned aerial vehicle （UAV） low-height remote sensing technique, which is flexible, efficient with low cost and with high resolution, is widely applied to investing various resources. Based on this, a novel extraction method for cultivated land information based on Deep Convolutional Neural Network and Transfer Learning （DTCLE） was proposed. First, linear features （roads and ridges etc.） were excluded based on Deep Convolutional Neural Network （DCNN）. Next, feature extraction method learned from DCNN was used to cultivated land information extraction by introducing transfer learning mechanism. Last, cultivated land information extraction results were completed by the DTCLE and eCognifion for cultivated land information extraction （ECLE）. The location of the Pengzhou County and Guanghan County, Sichuan Province were selected for the experimental purpose. The experimental results showed that the overall precision for the experimental image 1, 2 and 3 （of extracting cultivated land） with the DTCLE method was 91.7%, 88.1% and 88.2% respectively, and the overall precision of ECLE is 9o.7%, 90.5% and 87.0%, respectively. Accuracy of DTCLE was equivalent to that of ECLE, and also outperformed ECLE in terms of integrity and continuity.

AN LBP-BASED MULTI-SCALE ILLUMINATION PREPROCESSING METHOD FOR FACE RECOGNITION

It is one of the major challenges for face recognition to minimize the disadvantage of il- lumination variations of face images in different scenarios. Local Binary Pattern (LBP) has been proved to be successful for face recognition. However, it is still very rare to take LBP as an illumination preprocessing approach. In this paper, we propose a new LBP-based multi-scale illumination pre- processing method. This method mainly includes three aspects: threshold adjustment, multi-scale addition and symmetry restoration/neighborhood replacement. Our experiment results show that the proposed method performs better than the existing LBP-based methods at the point of illumination preprocessing. Moreover, compared with some face image preprocessing methods, such as histogram equalization, Gamma transformation, Retinex, and simplified LBP operator, our method can effectively improve the robustness for face recognition against illumination variation, and achieve higher recog- nition rate.

Semi-supervised Long-tail Endoscopic Image Classification

Objective To explore the semi-supervised learning(SSL) algorithm for long-tail endoscopic image classification with limited annotations.Method We explored semi-supervised long-tail endoscopic image classification in HyperKvasir,the largest gastrointestinal public dataset with 23 diverse classes.Semi-supervised learning algorithm FixMatch was applied based on consistency regularization and pseudo-labeling.After splitting the training dataset and the test dataset at a ratio of 4:1,we sampled 20%,50%,and 100% labeled training data to test the classification with limited annotations.Results The classification performance was evaluated by micro-average and macro-average evaluation metrics,with the Mathews correlation coefficient(MCC) as the overall evaluation.SSL algorithm improved the classification performance,with MCC increasing from 0.8761 to 0.8850,from 0.8983 to 0.8994,and from 0.9075 to 0.9095 with 20%,50%,and 100% ratio of labeled training data,respectively.With a 20% ratio of labeled training data,SSL improved both the micro-average and macro-average classification performance;while for the ratio of 50% and 100%,SSL improved the micro-average performance but hurt macro-average performance.Through analyzing the confusion matrix and labeling bias in each class,we found that the pseudo-based SSL algorithm exacerbated the classifier’ s preference for the head class,resulting in improved performance in the head class and degenerated performance in the tail class.Conclusion SSL can improve the classification performance for semi-supervised long-tail endoscopic image classification,especially when the labeled data is extremely limited,which may benefit the building of assisted diagnosis systems for low-volume hospitals.However,the pseudo-labeling strategy may amplify the effect of class imbalance,which hurts the classification performance for the tail class.

A study on sampling strategies in the figure cognitive process

This study was aimed at investigating the sampling strategies for 2 types of figures: 3-D cubes and human faces. The research was focused on: (a) from where the sampling process started; (b) in what order the figures' features were sampled. The study consisted of 2 experiments: (a) sampling strategies for 3-D cubes; (b) sampling strategies for human faces. The results showed that: (a), for 3-D cubes, the first sampling was mostly located at the outline parts, rarely at the center part; while for human faces, the first sampling was mostly located at the hair and outline parts, rarely at the mouth or cheek parts, in most cases, the first sampling-position had no significant effects on cognitive performance and that (b), the sampling order, both for 3-D cubes and for human faces, was determined by the degree of difference among the sampled-features.

Thermal Infrared Salient Human Detection Model Combined with Thermal Features in Airport Terminal

Target detection in low light background is one of the main tasks of night patrol robots for airport terminal.However,if some algorithms can run on a robot platform with limited computing resources,it is difficult for these algorithms to ensure the detection accuracy of human body in the airport terminal. A novel thermal infrared salient human detection model combined with thermal features called TFSHD is proposed. The TFSHD model is still based on U-Net,but the decoder module structure and model lightweight have been redesigned. In order to improve the detection accuracy of the algorithm in complex scenes,a fusion module composed of thermal branch and saliency branch is added to the decoder of the TFSHD model. Furthermore,a predictive loss function that is more sensitive to high temperature regions of the image is designed. Additionally,for the sake of reducing the computing resource requirements of the algorithm,a model lightweight scheme that includes simplifying the encoder network structure and controlling the number of decoder channels is adopted. The experimental results on four data sets show that the proposed method can not only ensure high detection accuracy and robustness of the algorithm,but also meet the needs of real-time detection of patrol robots with detection speed above 40 f/s.

Separated Same Rectangle Feature for Face Detection

The paper proposes a new method of ＂Separated Same Rectangle Feature （SSRF）＂ for face detection. Generally, Haar-like feature is used to make an Adaboost training algorithm with strong classifier. Haar-like feature is composed of two or more attached same rectangles. Inefficiency of the Haar-like feature often results from two or more attached same rectangles. But the proposed SSRF are composed of two separated same rectangles. So, it is very flexible and detailed. Therefore it creates more accurate strong classifier than Haar-like feature. SSRF uses integral image to reduce execuive time. Haar-like feature calculates the Sanl of intmsities of pixels on two or more rectangles. But SSRF always calculates the stun of intensities of pixels on only two rectangles. The weak classifier of Ariaboost algorithm based on SSRF is fastex than one based on Haar-like feature. In the experiment, we use 1 000 face images and 1 000nm- face images for Adaboost training. The proposed SSRF shows about 0.9% higher acctwacy than Haar-like features.

Human Body Image Edge Detection Based on Wavelet Transform

Human dresses are different in thousands way. Human body image signals have big noise, a poor light and shade contrast and a narrow range of gray gradation distribution. The application of a traditional grads method or gray method to detect human body image edges can't obtain satisfactory results because of false detections and missed detections. According to the peculiarity of human body image, dyadic wavelet transform of cubic spline is successfully applied to detect the face and profile edges of human body image and Mallat algorithm is used in the wavelet decomposition in this paper.

THREE DIMENSIONAL DIGITIZATION OF HUMAN HEAD BY FUSING STRUCTURED LIGHT AND CONTOURS

Three dimensional digitization of human head is desired in many applications. In this paper, an information fusion based scheme is presented to obtain 3-D information of human head. Structured light technology is employed to measure depth. For the special reflection areas,in which the structured light stripe can not be detected directly, the shape of the structured light stripe can be calculated from the corresponding contour. By fusing the information of structured light and the contours, the problem of reflectance influence is solved, and the whole shape of head,including hair area, can be obtained. Some good results are obtained.

The Empty Face of the Self-portrait： Time, Specter, and Event in The Fourth Portrait by Meng-Hung Chung

This short paper aims to critically analyze a contemporary Taiwan Residents film, The Fourth Portrait, directed by Meng-Hung Chung, from the perspective of Delenzian theories. In Deleuze＇s two books on cinema, the discussion of images demonstrates the entangled juxtaposition of the three levels： brain-thought, cinema-screen, and world-images that compose the cinematic consciousness. Through the interacted movement-images and time-images, the film unfolds the storyline within the aesthetic pleasure of poetic sentiment that gradually leads the audience to learn that a wandering boy, Hsiao-Hsiang, after the death of his father, has had several adventurous encounters that gradually expose the secrecy of his traumatic family： His birth mother has no decent job and his step-father has killed his own brother. This broken family has been haunted by the shared guilt and the undead memory as Derrida famously claims that hauntology precedes ontology. As the past coexists with the present, Deleuze analyzes the concept of I, with a central fracture in its pure form of the past demonstrating an ontological enigma that remains forever a secret. When the director uses the four portraits to indicate the four important events of this wandering boy, he deliberately leaves empty the fourth portrait, the self-portrait of the boy; it remains as an incomplete piece which symbolizes an enigma of his own life. It shows certain constitutive unnamable forces acting within the boy that seduces him forever to painfully misrecognize himself.

Imagery in Pride and Prejudice

Within the theoretical framework of English rhetoric, this paper analyzes the effect of imagery as a rhetorical device by Jane Austenin the novel Pride and Prejudice （2006）. Instances are cited with the use of imagery respectively in character portraits, dialogues, and scenes. It proves that an integrated use of this rhetorical device is an important means for vivid and impressive accounts in literary works, for it helps to build up the context for characterization, presenting the characters alive and distinctive, and effectively reveal the theme of the novel, bringing about authentic feelings to readers.

Research on the Perceptual Law of Artificial Ants

Beginning with the analysis of the behavior of natural ants, this paper illuminates the principle and method that, by adopting image texture energy as pheromone and finding their way on the track of the pheromone, artificial ants have the ability to identify and remember through similar measurement of pheromone. Based on the quantity of experiments, this paper analyzes some factors that influence the ability of artificial ants and draws some conclusions about the law of ant perception.